diff --git a/.gitmodules b/.gitmodules index 97ffbf03be..a9cc40e785 100644 --- a/.gitmodules +++ b/.gitmodules @@ -1,3 +1,4 @@ [submodule "stan"] path = stan url = https://github.com/stan-dev/stan + branch = mpi_warmup_v2 diff --git a/examples/arK-arK/0.output.csv b/examples/arK-arK/0.output.csv new file mode 100644 index 0000000000..924c439db7 --- /dev/null +++ b/examples/arK-arK/0.output.csv @@ -0,0 +1,2059 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = arK_arK_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 400 +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 0 (Default) +# data +# file = arK-arK.data.R +# init = 2 (Default) +# random +# seed = 4220681 +# output +# file = 0.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,alpha,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +22.1903,0.666667,0.125,1,3,1,49.3507,0.0278142,-0.956396,0.945664,1.09822,-2.05357,1.6766,0.522921 +22.1903,0,7.84723,0,1,1,-21.1567,0.0278142,-0.956396,0.945664,1.09822,-2.05357,1.6766,0.522921 +22.1903,0,1.10816,0,1,1,-19.7263,0.0278142,-0.956396,0.945664,1.09822,-2.05357,1.6766,0.522921 +22.1903,0.00273206,0.0986461,1,3,1,-16.6858,0.0278142,-0.956396,0.945664,1.09822,-2.05357,1.6766,0.522921 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+272.381,0.995733,0.608748,3,7,0,-270.372,0.0110164,0.683156,0.500576,0.105034,-0.105213,-0.255976,0.151895 +269.506,0.725611,0.995715,2,3,0,-268.498,0.011398,0.655103,0.514223,0.216131,-0.206653,-0.25321,0.140976 +270.289,0.48404,0.848398,2,7,0,-260.701,-0.0118523,0.563384,0.538548,0.122928,-0.0486394,-0.256563,0.148145 +271.279,0.969507,0.40834,3,7,0,-265.811,0.0168204,0.757014,0.38168,0.120734,-0.123993,-0.214772,0.144977 +# num_warmup = 1000 +# Adaptation terminated +# Step size = 0.680102 +# Elements of inverse mass matrix: +# 0.000127479, 0.000114743, -0.000108771, -9.72244e-05, 4.99913e-05, 2.23374e-05, -1.97638e-05 +# 0.000114743, 0.00568649, -0.00407461, -0.00275858, -9.67449e-06, 0.0015476, -0.000109416 +# -0.000108771, -0.00407461, 0.00761956, -0.00237867, -0.00149557, 0.000333285, 7.07884e-05 +# -9.72244e-05, -0.00275858, -0.00237867, 0.00865113, -0.000991131, -0.00277518, 8.16748e-05 +# 4.99913e-05, -9.67449e-06, -0.00149557, -0.000991131, 0.00585902, -0.00337193, 0.000123976 +# 2.23374e-05, 0.0015476, 0.000333285, -0.00277518, -0.00337193, 0.00463449, -0.000161052 +# -1.97638e-05, -0.000109416, 7.07884e-05, 8.16748e-05, 0.000123976, -0.000161052, 0.00240052 +267.088,0.786268,0.680102,3,7,0,-264.745,0.0196035,0.753956,0.555346,-0.145113,-0.000139044,-0.250399,0.164669 +272.187,1,0.680102,2,3,0,-266.396,0.0156214,0.670063,0.481219,0.131538,-0.044456,-0.31843,0.154172 +273.424,0.97233,0.680102,2,7,0,-271.038,0.007687,0.666008,0.472987,0.152653,-0.0847659,-0.308707,0.152424 +273.424,0.598376,0.680102,2,3,0,-266.987,0.007687,0.666008,0.472987,0.152653,-0.0847659,-0.308707,0.152424 +272.323,0.855664,0.680102,3,7,0,-270.339,-0.0122037,0.702745,0.428703,0.00245431,0.0693368,-0.307037,0.145457 +271.379,0.856573,0.680102,3,7,0,-268.8,-0.00461949,0.747425,0.374627,-0.0276143,0.0128236,-0.208884,0.147741 +272.581,1,0.680102,3,7,0,-270.026,-0.00915663,0.654402,0.452031,0.184469,-0.080538,-0.340873,0.148229 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+271.57,0.862097,0.680102,3,7,0,-261.489,-0.0117302,0.660096,0.536785,0.0834811,-0.00130646,-0.367634,0.141487 +271.187,0.955093,0.680102,3,7,0,-268.752,-0.0149498,0.738553,0.34162,0.134957,-0.115634,-0.220849,0.149362 +270.796,0.852479,0.680102,3,7,0,-266.599,0.000499936,0.6165,0.557246,0.0752609,0.07232,-0.393862,0.153305 +# +# Elapsed Time: 0.298234 seconds (Warm-up) +# 0.222138 seconds (Sampling) +# 0.520372 seconds (Total) +# diff --git a/examples/arK-arK/1.output.csv b/examples/arK-arK/1.output.csv new file mode 100644 index 0000000000..b2db92d7d2 --- /dev/null +++ b/examples/arK-arK/1.output.csv @@ -0,0 +1,2059 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = arK_arK_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 400 +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 1 +# data +# file = arK-arK.data.R +# init = 2 (Default) +# random +# seed = 4220681 +# output +# file = 1.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,alpha,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +-279.361,1,0.03125,3,7,0,612.617,-1.68381,1.52363,-1.9451,-1.40719,1.02855,-1.57893,1.77579 +-279.361,0,14.3855,0,1,1,282.098,-1.68381,1.52363,-1.9451,-1.40719,1.02855,-1.57893,1.77579 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+273.497,0.871019,0.519023,3,7,0,-269.359,0.00340758,0.651289,0.451233,0.120415,-0.0222793,-0.288039,0.149935 +271.457,0.898101,0.629975,2,3,0,-271.229,0.00370401,0.60347,0.423448,0.18091,0.0145261,-0.308689,0.146845 +273.194,1,0.813503,2,3,0,-270.889,0.00340314,0.671325,0.396532,0.202149,-0.0535522,-0.336899,0.150718 +266.931,0.247651,1.33309,2,3,0,-266.545,-0.0152491,0.61466,0.654095,0.125641,-0.172713,-0.308881,0.139463 +# num_warmup = 1000 +# Adaptation terminated +# Step size = 0.678726 +# Elements of inverse mass matrix: +# 0.000120505, 3.74049e-05, -1.68574e-05, 1.37195e-05, -1.36872e-06, -5.08448e-07, -4.30694e-05 +# 3.74049e-05, 0.00454572, -0.0037645, -0.00155557, 0.000348671, 0.000863323, -0.00017537 +# -1.68574e-05, -0.0037645, 0.00782973, -0.00255444, -0.00208759, 0.000709404, 0.000202354 +# 1.37195e-05, -0.00155557, -0.00255444, 0.00765242, -0.001781, -0.00210309, -9.88992e-05 +# -1.36872e-06, 0.000348671, -0.00208759, -0.001781, 0.00759878, -0.00400675, 0.000122932 +# -5.08448e-07, 0.000863323, 0.000709404, -0.00210309, -0.00400675, 0.00486872, -3.66339e-05 +# -4.30694e-05, -0.00017537, 0.000202354, -9.88992e-05, 0.000122932, -3.66339e-05, 0.00256502 +266.015,0.996586,0.678726,3,7,0,-264.171,0.00966003,0.755281,0.192209,0.101375,0.122785,-0.277406,0.161233 +273.068,0.96482,0.678726,2,3,0,-264.558,-0.013638,0.641014,0.475361,0.110147,-0.0585619,-0.277537,0.148608 +273.539,0.862554,0.678726,2,3,0,-270.478,-0.00159068,0.653423,0.459918,0.166731,-0.0513404,-0.334743,0.154441 +272.141,0.92105,0.678726,3,7,0,-271.133,0.00262721,0.733705,0.37762,0.194078,-0.161753,-0.237269,0.155129 +271.035,0.933253,0.678726,3,7,0,-269.151,0.0131523,0.715613,0.451699,0.0358549,0.0635586,-0.384303,0.141826 +269.518,0.869414,0.678726,3,7,0,-265.947,-0.0198622,0.695632,0.402557,0.163357,-0.146978,-0.183623,0.155461 +270.395,0.998249,0.678726,3,7,0,-266.298,0.0189019,0.698224,0.444899,0.0362145,0.066042,-0.373731,0.144803 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+271.601,1,0.678726,2,3,0,-268.853,-0.0105606,0.693285,0.461559,0.119884,-0.0800685,-0.251235,0.146118 +271.413,0.995524,0.678726,3,7,0,-269.423,0.00806025,0.656566,0.432501,0.106666,0.0200798,-0.363846,0.148309 +270.365,0.96484,0.678726,3,7,0,-268.713,0.002486,0.773032,0.355849,0.183163,-0.166431,-0.203188,0.153368 +# +# Elapsed Time: 0.281673 seconds (Warm-up) +# 0.224215 seconds (Sampling) +# 0.505888 seconds (Total) +# diff --git a/examples/arK-arK/2.output.csv b/examples/arK-arK/2.output.csv new file mode 100644 index 0000000000..c4d0547982 --- /dev/null +++ b/examples/arK-arK/2.output.csv @@ -0,0 +1,2059 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = arK_arK_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 400 +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 2 +# data +# file = arK-arK.data.R +# init = 2 (Default) +# random +# seed = 4220681 +# output +# file = 2.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,alpha,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +-120.651,1,0.125,1,1,0,350.576,-0.583139,0.336065,1.13456,-0.101018,-0.158459,-1.24484,1.67406 +-120.651,0,14.3855,0,1,1,121.443,-0.583139,0.336065,1.13456,-0.101018,-0.158459,-1.24484,1.67406 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+271.851,1,1.00485,2,3,0,-268.392,-0.000187106,0.728714,0.492786,-0.0753719,0.0726337,-0.311333,0.149098 +272.577,0.441442,1.662,2,3,0,-269.947,-0.00817513,0.664011,0.39116,0.197224,-0.0392762,-0.297076,0.153294 +272.771,0.980922,0.71216,3,7,0,-271.35,0.00596179,0.707513,0.500412,0.0290795,-0.0278558,-0.320314,0.143737 +269.657,0.262298,1.12012,2,3,0,-266.306,-0.0232229,0.674502,0.401308,0.194142,-0.138891,-0.215214,0.145409 +270.173,0.981705,0.318187,4,15,0,-266.145,0.0115918,0.758007,0.462431,0.0929093,-0.126881,-0.308734,0.155149 +# num_warmup = 1000 +# Adaptation terminated +# Step size = 0.708863 +# Elements of inverse mass matrix: +# 0.000109264, 4.37218e-05, 8.83219e-06, 7.00355e-07, -0.000120474, 7.36158e-05, -4.41317e-05 +# 4.37218e-05, 0.00549841, -0.00420412, -0.00234517, -0.000248915, 0.00160812, -0.000205142 +# 8.83219e-06, -0.00420412, 0.00741574, -0.00197612, -0.00157932, 0.000394054, 0.000156656 +# 7.00355e-07, -0.00234517, -0.00197612, 0.00841589, -0.00143995, -0.00286094, 0.000350983 +# -0.000120474, -0.000248915, -0.00157932, -0.00143995, 0.00760685, -0.00426103, -0.000365454 +# 7.36158e-05, 0.00160812, 0.000394054, -0.00286094, -0.00426103, 0.00544125, 5.63809e-05 +# -4.41317e-05, -0.000205142, 0.000156656, 0.000350983, -0.000365454, 5.63809e-05, 0.00219673 +270.302,0.958635,0.708863,3,7,0,-266.61,0.00464865,0.755313,0.330587,0.206827,-0.129427,-0.221903,0.145711 +268.704,0.657969,0.708863,3,7,0,-262.181,-0.01233,0.578271,0.604863,0.0134378,0.0725921,-0.410104,0.155322 +270.08,0.952503,0.708863,3,7,0,-265.439,0.01265,0.810809,0.265957,0.155914,-0.0784416,-0.223957,0.150504 +267.788,0.862542,0.708863,3,7,0,-264.949,-0.00786132,0.55366,0.544566,0.110375,-0.0935248,-0.273768,0.164048 +267.286,0.969765,0.708863,2,7,0,-265.952,-0.0021694,0.507509,0.590048,0.104177,-0.0483995,-0.309018,0.164376 +270.479,0.807163,0.708863,3,7,0,-260.856,-0.0154818,0.716874,0.44799,0.0558834,0.0217462,-0.344427,0.134167 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+267.423,0.977833,0.708863,3,7,0,-264.745,-0.00944814,0.767961,0.365769,-0.119131,0.0779925,-0.226833,0.150976 +267.363,0.966066,0.708863,3,7,0,-264.69,-0.00739045,0.783031,0.407717,-0.168545,0.0575933,-0.190988,0.144623 +271.25,0.980115,0.708863,2,7,0,-264.9,-0.00174579,0.779504,0.408975,-0.0809665,0.0847137,-0.299886,0.152894 +273.24,0.99378,0.708863,2,7,0,-270.678,0.00786317,0.760985,0.394905,0.0577562,-0.0600552,-0.250621,0.150971 +# +# Elapsed Time: 0.304654 seconds (Warm-up) +# 0.22252 seconds (Sampling) +# 0.527174 seconds (Total) +# diff --git a/examples/arK-arK/3.output.csv b/examples/arK-arK/3.output.csv new file mode 100644 index 0000000000..5c7ad6cb3d --- /dev/null +++ b/examples/arK-arK/3.output.csv @@ -0,0 +1,2059 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = arK_arK_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 400 +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 3 +# data +# file = arK-arK.data.R +# init = 2 (Default) +# random +# seed = 4220681 +# output +# file = 3.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,alpha,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +-213.724,1.091e-25,0.125,1,1,0,217.307,-0.665152,1.58668,-1.98146,-1.63131,1.13947,1.91236,2.83498 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+272.449,0.722262,0.728692,2,3,0,-266.894,-0.00126748,0.646433,0.47514,0.200197,-0.0799875,-0.323087,0.156695 +270.865,0.858826,0.618096,3,7,0,-268.846,-0.0151749,0.809169,0.346741,-0.00469372,0.0260296,-0.258052,0.157033 +272.336,0.971838,0.726479,3,7,0,-268.952,0.00482915,0.635086,0.48605,0.181348,-0.145159,-0.239817,0.148007 +# num_warmup = 1000 +# Adaptation terminated +# Step size = 0.697071 +# Elements of inverse mass matrix: +# 0.000116808, 4.17074e-05, -8.05124e-05, 0.000148633, -6.40787e-05, -4.69698e-05, -1.02627e-05 +# 4.17074e-05, 0.00483387, -0.00373964, -0.00238244, 0.000284907, 0.0013057, 0.000306582 +# -8.05124e-05, -0.00373964, 0.00732677, -0.00187376, -0.00168018, 0.000145892, -0.000512656 +# 0.000148633, -0.00238244, -0.00187376, 0.00867657, -0.00248692, -0.00227754, 6.66845e-05 +# -6.40787e-05, 0.000284907, -0.00168018, -0.00248692, 0.00764389, -0.00369825, 4.36866e-06 +# -4.69698e-05, 0.0013057, 0.000145892, -0.00227754, -0.00369825, 0.00488444, 0.000101566 +# 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+272.486,0.955914,0.697071,2,7,0,-269.25,-0.00177725,0.711536,0.501951,-0.00657277,-0.00362364,-0.271175,0.149774 +272.112,0.964501,0.697071,3,7,0,-270.286,0.000625051,0.697941,0.558853,0.0218197,-0.097959,-0.258179,0.153501 +# +# Elapsed Time: 0.300088 seconds (Warm-up) +# 0.228212 seconds (Sampling) +# 0.5283 seconds (Total) +# diff --git a/examples/arK-arK/arK-arK.data.R b/examples/arK-arK/arK-arK.data.R new file mode 100644 index 0000000000..44651956ff --- /dev/null +++ b/examples/arK-arK/arK-arK.data.R @@ -0,0 +1,46 @@ +K <- 5 + +T <- 200 + +y <- c( + 0.7293852753, 0.8297635923, 0.7839527091, 1.0259589105, 0.9696824412, + 1.0828859218, 0.7063891465, 0.7769243971, 0.4618029476, 0.6385997565, + 0.3742344429, 0.0854966416, -0.1260149233, -0.2934151326, -0.2617308802, + -0.3359221372, -0.5019895766, -0.6417399532, -0.6224629523, -0.8508997238, + -0.8678351807, -1.0163853144, -1.0558901454, -0.9694812319, -1.0672519169, + -0.8430989055, -0.6827006149, -0.4446573489, -0.5920387090, -0.5105689815, + -0.4178858435, -0.1736168751, -0.1072500940, -0.0355025516, 0.3432168459, + 0.3841903414, 0.4960876950, 0.7084511605, 0.5962806615, 0.6414424152, + 0.6513222735, 0.5942153484, 0.7779414176, 0.7307762325, 0.4822472694, + 0.5320372234, 0.4851022175, 0.3685521219, 0.3533268113, 0.1633690002, + 0.2530389410, 0.0006621430, -0.0157674958, -0.0144909054, -0.0252628993, + -0.0056256128, -0.3189177332, -0.0227791612, -0.0716865707, -0.1850182514, + -0.2350075682, -0.1243111880, -0.1304923565, -0.1994777726, 0.0775739320, + -0.1628522111, 0.0234645663, -0.0646807914, 0.0845324981, 0.0550150773, + 0.1417424074, 0.0876638222, -0.0528467198, 0.0695217092, -0.1014499970, + -0.0688806547, -0.2512073227, -0.3902872828, -0.1676283611, -0.2791635517, + -0.3121253506, -0.2865502547, -0.4117701622, -0.4982098458, -0.5028522787, + -0.7394004480, -0.2492280924, -0.4710158859, -0.4645727076, -0.4457058117, + -0.2844237121, -0.0227786998, -0.0605507196, 0.0662256249, 0.1405232927, + 0.2763394882, 0.3772233671, 0.6103044598, 0.8808694697, 0.7885174270, + 0.8013632395, 0.6609678195, 0.8097669196, 0.8205077274, 0.9807562966, + 0.7240388847, 0.9318587166, 0.8504881551, 0.4805918638, 0.5085811342, + 0.4161126092, 0.3146685518, -0.0281539189, -0.0717016521, -0.1439206592, + -0.5223661051, -0.4033621109, -0.6886329349, -0.6947170572, -0.6496557077, + -0.9926992981, -0.9354098817, -0.8969864546, -0.9781523572, -1.0668406080, + -0.9535621424, -0.7570773682, -0.8425755431, -0.6977697431, -0.3165581858, + -0.3878217300, -0.0671166462, -0.0385154999, 0.0895646813, 0.1454578935, + 0.1852131654, 0.3956127617, 0.6852644284, 0.5563107812, 0.7108445288, + 0.7462804690, 0.6684519285, 0.6936535333, 0.7379992741, 0.6627708128, + 0.6900939802, 0.6807304694, 0.3733191989, 0.4536740601, 0.3137682260, + 0.4500334320, -0.0337947734, 0.0047340737, -0.0856874439, 0.1082543270, + -0.1398269720, -0.0429735449, -0.4541637356, -0.3326428149, -0.2333534103, + -0.2014612607, -0.1826792426, -0.2278848137, -0.0415383584, -0.1210077677, + -0.0724354048, -0.0482025571, 0.1580149098, 0.0583926960, -0.1117559432, + -0.0381725259, 0.1789819529, -0.0148415779, 0.0500966207, -0.1980592117, + -0.1400114013, -0.1746734639, -0.1767850853, -0.2154143864, -0.4144745850, + -0.3405434088, -0.4482790416, -0.6571159536, -0.3546433053, -0.5257081174, + -0.6564372310, -0.5245263017, -0.4758655851, -0.3631316786, -0.3366915389, + -0.3254437415, 0.0006694692, 0.2080422414, 0.0023164951, 0.1124752107, + 0.3494037146, 0.4717023945, 0.5906600432, 0.6048634064, 0.9331979099) + diff --git a/examples/arK-arK/arK-arK.stan b/examples/arK-arK/arK-arK.stan new file mode 100644 index 0000000000..d3177c889c --- /dev/null +++ b/examples/arK-arK/arK-arK.stan @@ -0,0 +1,27 @@ +data { + int K; + int T; + real y[T]; +} + +parameters { + real alpha; + real beta[K]; + real sigma; +} + +model { + alpha ~ normal(0, 10); + beta ~ normal(0, 10); + sigma ~ cauchy(0, 2.5); + + for (t in (K+1):T) { + real mu; + mu = alpha; + + for (k in 1:K) + mu = mu + beta[k] * y[t - k]; + + y[t] ~ normal(mu, sigma); + } +} diff --git a/examples/arK-arK/mpi.0.output.csv b/examples/arK-arK/mpi.0.output.csv new file mode 100644 index 0000000000..44e0a0d39d --- /dev/null +++ b/examples/arK-arK/mpi.0.output.csv @@ -0,0 +1,1509 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = arK_arK_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 400 +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 0 (Default) +# data +# file = arK-arK.data.R +# init = 2 (Default) +# random +# seed = 4220681 +# output +# file = mpi.0.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,alpha,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +22.1903,0.666667,0.125,1,3,1,49.3507,0.0278142,-0.956396,0.945664,1.09822,-2.05357,1.6766,0.522921 +22.1903,0,7.84723,0,1,1,-21.1567,0.0278142,-0.956396,0.945664,1.09822,-2.05357,1.6766,0.522921 +22.1903,0,1.10816,0,1,1,-19.7263,0.0278142,-0.956396,0.945664,1.09822,-2.05357,1.6766,0.522921 +22.1903,0.00273206,0.0986461,1,3,1,-16.6858,0.0278142,-0.956396,0.945664,1.09822,-2.05357,1.6766,0.522921 +31.926,1,0.00724311,5,31,0,-18.7341,-0.031095,-0.827898,1.10387,1.17401,-2.04308,1.6466,0.539781 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0.198347 seconds (Warm-up) +# 0.19701 seconds (Sampling) +# 0.395357 seconds (Total) +# diff --git a/examples/arK-arK/mpi.1.output.csv b/examples/arK-arK/mpi.1.output.csv new file mode 100644 index 0000000000..52e01580d0 --- /dev/null +++ b/examples/arK-arK/mpi.1.output.csv @@ -0,0 +1,1509 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = arK_arK_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 400 +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 1 +# data +# file = arK-arK.data.R +# init = 2 (Default) +# random +# seed = 4220681 +# output +# file = mpi.1.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,alpha,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +-279.361,1,0.03125,3,7,0,612.617,-1.68381,1.52363,-1.9451,-1.40719,1.02855,-1.57893,1.77579 +-279.361,0,14.3855,0,1,1,282.098,-1.68381,1.52363,-1.9451,-1.40719,1.02855,-1.57893,1.77579 +-279.361,0,2.43117,0,1,1,283.581,-1.68381,1.52363,-1.9451,-1.40719,1.02855,-1.57893,1.77579 +-279.361,0,0.239791,1,1,0,280.875,-1.68381,1.52363,-1.9451,-1.40719,1.02855,-1.57893,1.77579 +-252.974,0.96457,0.0186273,2,3,0,284.429,-1.62658,1.65173,-1.90799,-1.40895,1.02266,-1.458,2.00056 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terminated +# Step size = 0.697818 +# Elements of inverse mass matrix: +# 0.000120742, 4.23576e-05, 2.15494e-05, -9.79007e-05, -1.47291e-05, 9.1708e-05, 3.95446e-05 +# 4.23576e-05, 0.00474569, -0.00380363, -0.0018781, 0.000314314, 0.00102417, -2.69482e-05 +# 2.15494e-05, -0.00380363, 0.00776258, -0.00220265, -0.00238104, 0.000560488, 0.000387583 +# -9.79007e-05, -0.0018781, -0.00220265, 0.00788815, -0.00190806, -0.00205619, -0.000440942 +# -1.47291e-05, 0.000314314, -0.00238104, -0.00190806, 0.00844429, -0.00455065, 2.38452e-05 +# 9.1708e-05, 0.00102417, 0.000560488, -0.00205619, -0.00455065, 0.00550677, 7.89365e-05 +# 3.95446e-05, -2.69482e-05, 0.000387583, -0.000440942, 2.38452e-05, 7.89365e-05, 0.00270335 +271.512,0.960855,0.697818,3,7,0,-266.845,-0.0193759,0.632445,0.516804,0.103769,-0.074243,-0.308542,0.151183 +269.959,0.835527,0.697818,3,7,0,-266.044,-0.00564327,0.766236,0.514902,0.0165891,-0.165188,-0.190146,0.155767 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a/examples/arK-arK/mpi.2.output.csv b/examples/arK-arK/mpi.2.output.csv new file mode 100644 index 0000000000..9ada3024d3 --- /dev/null +++ b/examples/arK-arK/mpi.2.output.csv @@ -0,0 +1,1509 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = arK_arK_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 400 +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 2 +# data +# file = arK-arK.data.R +# init = 2 (Default) +# random +# seed = 4220681 +# output +# file = mpi.2.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,alpha,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +-120.651,1,0.125,1,1,0,350.576,-0.583139,0.336065,1.13456,-0.101018,-0.158459,-1.24484,1.67406 +-120.651,0,14.3855,0,1,1,121.443,-0.583139,0.336065,1.13456,-0.101018,-0.158459,-1.24484,1.67406 +-120.651,0,2.43117,0,1,1,123.64,-0.583139,0.336065,1.13456,-0.101018,-0.158459,-1.24484,1.67406 +-120.651,0,0.239791,0,1,1,125.569,-0.583139,0.336065,1.13456,-0.101018,-0.158459,-1.24484,1.67406 +-94.9491,1,0.0186273,2,3,0,122.667,-0.541079,0.392859,1.12345,-0.103113,-0.138451,-1.20407,1.44531 +99.0527,0.950697,0.0257257,3,7,0,87.3225,0.218965,0.175995,1.54584,0.326138,-0.00707652,-0.880057,0.286516 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4.23576e-05, 2.15494e-05, -9.79007e-05, -1.47291e-05, 9.1708e-05, 3.95446e-05 +# 4.23576e-05, 0.00474569, -0.00380363, -0.0018781, 0.000314314, 0.00102417, -2.69482e-05 +# 2.15494e-05, -0.00380363, 0.00776258, -0.00220265, -0.00238104, 0.000560488, 0.000387583 +# -9.79007e-05, -0.0018781, -0.00220265, 0.00788815, -0.00190806, -0.00205619, -0.000440942 +# -1.47291e-05, 0.000314314, -0.00238104, -0.00190806, 0.00844429, -0.00455065, 2.38452e-05 +# 9.1708e-05, 0.00102417, 0.000560488, -0.00205619, -0.00455065, 0.00550677, 7.89365e-05 +# 3.95446e-05, -2.69482e-05, 0.000387583, -0.000440942, 2.38452e-05, 7.89365e-05, 0.00270335 +266.537,0.889447,1.06512,2,3,0,-262.242,-0.00494851,0.534468,0.512788,0.314939,-0.0603131,-0.35447,0.149993 +269.898,0.998891,1.06512,2,3,0,-263.549,0.0179593,0.650561,0.553597,0.0168353,-0.0580346,-0.225728,0.149773 +270.186,1,1.06512,2,3,0,-267.682,0.0166357,0.593616,0.484083,0.183505,-0.0505624,-0.287519,0.156857 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0000000000..ffda588a8f --- /dev/null +++ b/examples/arK-arK/mpi.3.output.csv @@ -0,0 +1,1509 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = arK_arK_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 400 +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 3 +# data +# file = arK-arK.data.R +# init = 2 (Default) +# random +# seed = 4220681 +# output +# file = mpi.3.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,alpha,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +-213.724,1.091e-25,0.125,1,1,0,217.307,-0.665152,1.58668,-1.98146,-1.63131,1.13947,1.91236,2.83498 +-213.724,0,2.33506,0,1,1,215.052,-0.665152,1.58668,-1.98146,-1.63131,1.13947,1.91236,2.83498 +-213.724,0,0.230236,0,1,1,219.711,-0.665152,1.58668,-1.98146,-1.63131,1.13947,1.91236,2.83498 +-107.074,0.998694,0.0166944,3,7,0,217.154,-0.49228,1.45913,-2.00829,-1.52235,1.14521,1.92444,1.47273 +-76.8204,1,0.0185579,3,7,0,108.835,-0.414839,1.42897,-2.01804,-1.48546,1.2002,1.84084,1.18596 +-27.1739,0.877177,0.0256257,3,7,0,79.5318,0.0258454,1.30457,-1.91533,-1.49844,1.19249,1.90177,0.72641 +-29.7696,0.833519,0.0276306,4,31,1,35.1871,0.0627199,1.26843,-1.83241,-1.60257,1.11948,1.96646,0.755155 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+271.157,0.749278,1.04845,2,3,0,-267.875,-0.0106473,0.620706,0.429569,0.1846,0.0238637,-0.346733,0.138612 +269.929,0.695928,0.975768,2,3,0,-267.458,-0.00452314,0.548429,0.584331,0.0542866,-0.0346167,-0.241385,0.150183 +270.212,0.963977,0.837041,3,7,0,-266.476,-0.00452208,0.849624,0.334595,0.0842295,-0.0156426,-0.344893,0.146902 +# num_warmup = 450 +# Adaptation terminated +# Step size = 1.0833 +# Elements of inverse mass matrix: +# 0.000120742, 4.23576e-05, 2.15494e-05, -9.79007e-05, -1.47291e-05, 9.1708e-05, 3.95446e-05 +# 4.23576e-05, 0.00474569, -0.00380363, -0.0018781, 0.000314314, 0.00102417, -2.69482e-05 +# 2.15494e-05, -0.00380363, 0.00776258, -0.00220265, -0.00238104, 0.000560488, 0.000387583 +# -9.79007e-05, -0.0018781, -0.00220265, 0.00788815, -0.00190806, -0.00205619, -0.000440942 +# -1.47291e-05, 0.000314314, -0.00238104, -0.00190806, 0.00844429, -0.00455065, 2.38452e-05 +# 9.1708e-05, 0.00102417, 0.000560488, -0.00205619, -0.00455065, 0.00550677, 7.89365e-05 +# 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+271.911,0.722485,1.0833,2,3,0,-270.953,-0.00193618,0.726666,0.501905,0.0839437,-0.14569,-0.273401,0.155723 +270.662,0.450357,1.0833,2,3,0,-265.644,0.00724072,0.677902,0.36664,0.145926,-0.0451107,-0.296768,0.151588 +# +# Elapsed Time: 0.197937 seconds (Warm-up) +# 0.142598 seconds (Sampling) +# 0.340535 seconds (Total) +# diff --git a/examples/arK/0.output.csv b/examples/arK/0.output.csv new file mode 100644 index 0000000000..1e3ada2b18 --- /dev/null +++ b/examples/arK/0.output.csv @@ -0,0 +1,2059 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = arK_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 0 (Default) +# data +# file = arK.data.R +# init = 2 (Default) +# random +# seed = 4809463 +# output +# file = 0.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,alpha,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +28.1904,1,0.125,1,1,0,111.864,0.256249,1.03091,0.0919795,-0.187369,-1.12116,1.4515,0.722111 +28.1904,0,14.3855,0,1,1,-24.587,0.256249,1.03091,0.0919795,-0.187369,-1.12116,1.4515,0.722111 +28.1904,0,2.43117,0,1,1,-23.719,0.256249,1.03091,0.0919795,-0.187369,-1.12116,1.4515,0.722111 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+263.52,0.848457,0.361672,3,7,0,-261.752,-0.0338112,0.702128,0.249771,0.198494,0.127287,-0.430047,0.1529 +270.716,1,0.414042,3,7,0,-260.187,-0.0253228,0.668465,0.433406,0.190068,-0.0438277,-0.334806,0.146373 +269.809,0.797391,0.681143,3,7,0,-265.165,-0.0188816,0.771973,0.414091,0.16519,-0.150583,-0.277154,0.155342 +270.326,0.95758,0.685841,3,7,0,-266.544,0.0224076,0.767689,0.318774,0.150224,-0.0479067,-0.30558,0.149949 +267.097,0.631529,1.00976,2,3,0,-263.124,-0.00820018,0.704169,0.585298,-0.209291,0.0833313,-0.246473,0.147953 +# num_warmup = 1000 +# Adaptation terminated +# Step size = 0.618499 +# Elements of inverse mass matrix: +# 0.000116568, -3.1532e-06, 3.70575e-05, 4.33032e-05, -5.22457e-05, -7.08822e-06, 4.28491e-05 +# -3.1532e-06, 0.00509433, -0.00412709, -0.00197129, 0.000439437, 0.000897434, 0.000128219 +# 3.70575e-05, -0.00412709, 0.00797201, -0.0024042, -0.00166856, 0.000211263, 0.000165066 +# 4.33032e-05, -0.00197129, -0.0024042, 0.00842815, -0.00263216, -0.00156095, 7.50522e-05 +# -5.22457e-05, 0.000439437, -0.00166856, -0.00263216, 0.00726873, -0.00331345, -0.000156018 +# -7.08822e-06, 0.000897434, 0.000211263, -0.00156095, -0.00331345, 0.0040455, -9.27123e-05 +# 4.28491e-05, 0.000128219, 0.000165066, 7.50522e-05, -0.000156018, -9.27123e-05, 0.0027622 +267.796,1,0.618499,3,7,0,-265.732,0.00798354,0.684513,0.301383,0.400586,-0.152159,-0.352325,0.154076 +271.909,1,0.618499,2,7,0,-267.007,0.00527332,0.722507,0.361043,0.185278,-0.0673804,-0.335676,0.151893 +269.31,0.906833,0.618499,3,7,0,-267.485,-0.0187949,0.584144,0.455462,0.151697,-0.0541113,-0.2336,0.150394 +270.331,1,0.618499,3,7,0,-267.242,0.00626469,0.817135,0.388547,0.0577878,-0.0739026,-0.308349,0.155961 +262.236,0.744739,0.618499,2,3,0,-259.922,0.0150274,0.497431,0.554415,0.256757,0.0234216,-0.413192,0.131163 +271.469,1,0.618499,2,3,0,-259.771,-0.00585104,0.763101,0.292855,0.154958,-0.0269267,-0.263267,0.14136 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+272.221,0.99599,0.618499,3,7,0,-269.223,0.00529079,0.811178,0.354684,0.00525091,0.0185193,-0.292135,0.149761 +270.447,0.915423,0.618499,2,7,0,-269.302,0.00248768,0.566387,0.471738,0.325158,-0.111194,-0.34774,0.152842 +270.265,0.993593,0.618499,3,7,0,-269.241,-0.00557203,0.818552,0.404913,-0.106723,0.0234658,-0.24296,0.143688 +271.767,1,0.618499,3,7,0,-268.31,0.0196132,0.636435,0.455798,0.129357,-0.0393511,-0.284214,0.149235 +# +# Elapsed Time: 0.299603 seconds (Warm-up) +# 0.23163 seconds (Sampling) +# 0.531233 seconds (Total) +# diff --git a/examples/arK/1.output.csv b/examples/arK/1.output.csv new file mode 100644 index 0000000000..415355b131 --- /dev/null +++ b/examples/arK/1.output.csv @@ -0,0 +1,2059 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = arK_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 1 +# data +# file = arK.data.R +# init = 2 (Default) +# random +# seed = 4809463 +# output +# file = 1.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,alpha,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +-279.297,1,0.0625,2,3,0,310.854,0.131107,1.63742,1.705,1.76975,-0.281715,1.28629,2.74101 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+268.818,0.376189,1.48547,2,3,0,-267.221,0.0114025,0.715247,0.470918,0.196011,-0.0790908,-0.375803,0.163163 +268.485,0.935816,0.544102,3,7,0,-263.386,-0.0188745,0.582583,0.380763,0.219377,0.116796,-0.410302,0.148531 +269.096,0.92402,0.762238,2,7,0,-264.277,-0.000796705,0.641976,0.364972,0.307327,-0.0736627,-0.372034,0.166325 +# num_warmup = 1000 +# Adaptation terminated +# Step size = 0.766353 +# Elements of inverse mass matrix: +# 0.000109675, -1.01528e-06, -2.92695e-05, -1.73906e-05, 2.2211e-05, 9.57263e-06, 1.95279e-05 +# -1.01528e-06, 0.00569834, -0.00393522, -0.00305955, -0.000268173, 0.00215925, -0.000152056 +# -2.92695e-05, -0.00393522, 0.00775256, -0.00227074, -0.000525429, -0.00107267, -3.34253e-05 +# -1.73906e-05, -0.00305955, -0.00227074, 0.00934755, -0.00213425, -0.00220061, 0.000526042 +# 2.2211e-05, -0.000268173, -0.000525429, -0.00213425, 0.00651707, -0.00360871, -0.000457106 +# 9.57263e-06, 0.00215925, -0.00107267, -0.00220061, -0.00360871, 0.00514916, 0.00016271 +# 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+272.674,0.962909,0.766353,3,7,0,-268.98,0.00666974,0.671527,0.439295,0.104459,0.0131952,-0.316986,0.138422 +270.703,0.627084,0.766353,2,3,0,-267.297,0.0172441,0.659397,0.377022,0.192296,0.0691935,-0.380586,0.151561 +# +# Elapsed Time: 0.294309 seconds (Warm-up) +# 0.205803 seconds (Sampling) +# 0.500112 seconds (Total) +# diff --git a/examples/arK/2.output.csv b/examples/arK/2.output.csv new file mode 100644 index 0000000000..751a61b9ba --- /dev/null +++ b/examples/arK/2.output.csv @@ -0,0 +1,2059 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = arK_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 2 +# data +# file = arK.data.R +# init = 2 (Default) +# random +# seed = 4809463 +# output +# file = 2.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,alpha,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +-140.604,0.571429,0.03125,3,7,0,1236.89,0.862277,0.4908,-1.38349,0.512083,1.29839,-1.03519,1.69909 +-140.604,0,6.59954,0,1,1,148.861,0.862277,0.4908,-1.38349,0.512083,1.29839,-1.03519,1.69909 +-140.604,0,0.885342,0,1,1,142.095,0.862277,0.4908,-1.38349,0.512083,1.29839,-1.03519,1.69909 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+271.02,0.95489,0.634587,3,7,0,-269.392,-0.0174926,0.628596,0.461556,0.154255,-0.0587721,-0.324181,0.157366 +272.607,0.992482,0.940746,2,3,0,-269.659,-0.016978,0.69909,0.45176,0.109862,-0.0656306,-0.280384,0.153488 +272.607,0.0271208,1.5173,1,1,0,-270.063,-0.016978,0.69909,0.45176,0.109862,-0.0656306,-0.280384,0.153488 +268.309,0.97598,0.246034,4,15,0,-267.652,0.0264117,0.596363,0.504926,0.235775,-0.149752,-0.315305,0.147668 +# num_warmup = 1000 +# Adaptation terminated +# Step size = 0.605609 +# Elements of inverse mass matrix: +# 0.000140585, -5.58805e-05, 7.60955e-05, -7.1156e-06, 6.13054e-05, -7.13729e-05, -2.59421e-05 +# -5.58805e-05, 0.00429297, -0.00319087, -0.00250598, 0.000796223, 0.000900218, -0.000160209 +# 7.60955e-05, -0.00319087, 0.00647827, -0.00183872, -0.00164461, 0.000302926, 6.20364e-05 +# -7.1156e-06, -0.00250598, -0.00183872, 0.00908057, -0.00312587, -0.00187128, 0.000104534 +# 6.13054e-05, 0.000796223, -0.00164461, -0.00312587, 0.00758158, -0.00354142, -0.000241824 +# -7.13729e-05, 0.000900218, 0.000302926, -0.00187128, -0.00354142, 0.0045963, 0.000197452 +# -2.59421e-05, -0.000160209, 6.20364e-05, 0.000104534, -0.000241824, 0.000197452, 0.00268774 +270.784,0.983199,0.605609,3,7,0,-265.526,0.014502,0.686948,0.43704,0.0442755,-0.00951752,-0.298651,0.157001 +271.907,0.966339,0.605609,3,7,0,-268.713,-0.00824978,0.666448,0.502034,0.134655,-0.0406914,-0.327067,0.145084 +270.1,0.909509,0.605609,3,7,0,-268.315,0.00177994,0.649186,0.501792,0.0719886,0.134313,-0.431575,0.14512 +268.144,0.924057,0.605609,3,7,0,-264.83,0.00425168,0.611357,0.552376,0.155398,0.029124,-0.487037,0.146653 +268.43,1,0.605609,3,7,0,-264.907,-0.00599898,0.778066,0.293681,0.0908042,-0.0685292,-0.15207,0.157739 +268.878,0.996941,0.605609,3,7,0,-265.874,5.72105e-05,0.574439,0.602617,0.206683,-0.0785895,-0.425687,0.143393 +272.28,0.999996,0.605609,3,7,0,-267.786,0.00241698,0.711927,0.414166,0.0945755,-0.129157,-0.18581,0.155288 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+273.292,0.851039,0.605609,2,7,0,-270.886,-0.00206592,0.705938,0.436998,0.117969,-0.0235672,-0.31703,0.155241 +271.682,0.869304,0.605609,3,7,0,-270.015,-0.00555747,0.66255,0.518112,0.147223,-0.103561,-0.296096,0.158638 +272.295,0.936383,0.605609,3,7,0,-267.939,0.00664902,0.737007,0.410115,0.0185718,-0.0110194,-0.275933,0.141599 +# +# Elapsed Time: 0.302026 seconds (Warm-up) +# 0.228172 seconds (Sampling) +# 0.530198 seconds (Total) +# diff --git a/examples/arK/3.output.csv b/examples/arK/3.output.csv new file mode 100644 index 0000000000..fbdb8da7b7 --- /dev/null +++ b/examples/arK/3.output.csv @@ -0,0 +1,2059 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = arK_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 3 +# data +# file = arK.data.R +# init = 2 (Default) +# random +# seed = 4809463 +# output +# file = 3.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,alpha,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +-281.793,1,0.015625,2,3,0,993.964,0.766128,-0.428307,1.06034,-0.748586,-0.28334,0.980412,0.411667 +-281.793,0,14.3855,0,1,1,283.633,0.766128,-0.428307,1.06034,-0.748586,-0.28334,0.980412,0.411667 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+268.736,0.82969,0.674168,3,7,0,-266.623,-0.0158988,0.537312,0.622167,0.192702,-0.0311425,-0.415475,0.154506 +269.755,1,0.738064,3,7,0,-266.012,-0.0138989,0.744652,0.543375,0.0209635,-0.115346,-0.279389,0.159409 +268.328,0.839178,1.21551,2,3,0,-265.857,-0.0203817,0.561195,0.654166,0.0882198,-0.0851881,-0.290666,0.154655 +267.48,0.920732,1.35381,2,3,0,-263.905,0.00668096,0.876159,0.247718,-0.012091,0.0678815,-0.310923,0.14692 +267.48,8.08663e-08,1.82701,2,3,0,-261.883,0.00668096,0.876159,0.247718,-0.012091,0.0678815,-0.310923,0.14692 +# num_warmup = 1000 +# Adaptation terminated +# Step size = 0.712443 +# Elements of inverse mass matrix: +# 0.000114415, 6.86985e-05, -1.58848e-05, -0.000127436, 9.34933e-05, 1.306e-05, 1.3698e-05 +# 6.86985e-05, 0.00482708, -0.00428104, -0.00138609, 0.000110764, 0.00120017, -8.37397e-05 +# -1.58848e-05, -0.00428104, 0.00879316, -0.00250408, -0.00221176, 6.23422e-05, 0.000109509 +# -0.000127436, -0.00138609, -0.00250408, 0.00727011, -0.00188702, -0.00176953, -0.000124695 +# 9.34933e-05, 0.000110764, -0.00221176, -0.00188702, 0.00739788, -0.00335682, 0.000656985 +# 1.306e-05, 0.00120017, 6.23422e-05, -0.00176953, -0.00335682, 0.0043914, -0.000420955 +# 1.3698e-05, -8.37397e-05, 0.000109509, -0.000124695, 0.000656985, -0.000420955, 0.00272299 +268.664,0.917719,0.712443,3,7,0,-260.789,0.00351373,0.497232,0.600387,0.118285,0.0714331,-0.379393,0.155372 +271.406,1,0.712443,2,3,0,-266.997,0.00723993,0.601089,0.542959,0.0875429,-0.0102497,-0.29381,0.154536 +273.469,0.695058,0.712443,3,7,0,-265.212,-0.00490489,0.740888,0.440808,0.0391623,-0.0628539,-0.26636,0.146112 +270.604,0.736641,0.712443,2,3,0,-269.893,0.0203227,0.799198,0.334424,0.084125,0.0213586,-0.317874,0.153495 +272.546,0.939408,0.712443,3,7,0,-268.832,0.0109223,0.719832,0.434964,0.0507579,-0.0385019,-0.242054,0.14414 +271.361,0.510052,0.712443,2,3,0,-265.279,0.000930337,0.659081,0.596411,0.0198943,-0.0109302,-0.358114,0.151905 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+272.671,0.818075,0.712443,2,3,0,-269.405,-0.00299469,0.600885,0.527495,0.0736717,-0.0137021,-0.282652,0.148497 +272.194,0.925481,0.712443,3,7,0,-269.508,-0.00232242,0.786474,0.358631,0.120384,-0.0122866,-0.355728,0.145119 +271.523,0.780905,0.712443,3,7,0,-267.553,0.000613815,0.583804,0.485762,0.126406,-0.0417347,-0.290557,0.153277 +271.302,0.888956,0.712443,3,7,0,-268.15,-0.00740729,0.821298,0.269327,0.156011,-0.0772913,-0.266024,0.152389 +# +# Elapsed Time: 0.298624 seconds (Warm-up) +# 0.223106 seconds (Sampling) +# 0.52173 seconds (Total) +# diff --git a/examples/arK/arK.data.R b/examples/arK/arK.data.R new file mode 100644 index 0000000000..cfe95272f3 --- /dev/null +++ b/examples/arK/arK.data.R @@ -0,0 +1,46 @@ +K <- 5 + +T <- 200 + +y <- c( + 0.7293852753, 0.8297635923, 0.7839527091, 1.0259589105, 0.9696824412, + 1.0828859218, 0.7063891465, 0.7769243971, 0.4618029476, 0.6385997565, + 0.3742344429, 0.0854966416, -0.1260149233, -0.2934151326, -0.2617308802, +-0.3359221372, -0.5019895766, -0.6417399532, -0.6224629523, -0.8508997238, +-0.8678351807, -1.0163853144, -1.0558901454, -0.9694812319, -1.0672519169, +-0.8430989055, -0.6827006149, -0.4446573489, -0.5920387090, -0.5105689815, +-0.4178858435, -0.1736168751, -0.1072500940, -0.0355025516, 0.3432168459, + 0.3841903414, 0.4960876950, 0.7084511605, 0.5962806615, 0.6414424152, + 0.6513222735, 0.5942153484, 0.7779414176, 0.7307762325, 0.4822472694, + 0.5320372234, 0.4851022175, 0.3685521219, 0.3533268113, 0.1633690002, + 0.2530389410, 0.0006621430, -0.0157674958, -0.0144909054, -0.0252628993, +-0.0056256128, -0.3189177332, -0.0227791612, -0.0716865707, -0.1850182514, +-0.2350075682, -0.1243111880, -0.1304923565, -0.1994777726, 0.0775739320, +-0.1628522111, 0.0234645663, -0.0646807914, 0.0845324981, 0.0550150773, + 0.1417424074, 0.0876638222, -0.0528467198, 0.0695217092, -0.1014499970, +-0.0688806547, -0.2512073227, -0.3902872828, -0.1676283611, -0.2791635517, +-0.3121253506, -0.2865502547, -0.4117701622, -0.4982098458, -0.5028522787, +-0.7394004480, -0.2492280924, -0.4710158859, -0.4645727076, -0.4457058117, +-0.2844237121, -0.0227786998, -0.0605507196, 0.0662256249, 0.1405232927, + 0.2763394882, 0.3772233671, 0.6103044598, 0.8808694697, 0.7885174270, + 0.8013632395, 0.6609678195, 0.8097669196, 0.8205077274, 0.9807562966, + 0.7240388847, 0.9318587166, 0.8504881551, 0.4805918638, 0.5085811342, + 0.4161126092, 0.3146685518, -0.0281539189, -0.0717016521, -0.1439206592, +-0.5223661051, -0.4033621109, -0.6886329349, -0.6947170572, -0.6496557077, +-0.9926992981, -0.9354098817, -0.8969864546, -0.9781523572, -1.0668406080, +-0.9535621424, -0.7570773682, -0.8425755431, -0.6977697431, -0.3165581858, +-0.3878217300, -0.0671166462, -0.0385154999, 0.0895646813, 0.1454578935, + 0.1852131654, 0.3956127617, 0.6852644284, 0.5563107812, 0.7108445288, + 0.7462804690, 0.6684519285, 0.6936535333, 0.7379992741, 0.6627708128, + 0.6900939802, 0.6807304694, 0.3733191989, 0.4536740601, 0.3137682260, + 0.4500334320, -0.0337947734, 0.0047340737, -0.0856874439, 0.1082543270, +-0.1398269720, -0.0429735449, -0.4541637356, -0.3326428149, -0.2333534103, +-0.2014612607, -0.1826792426, -0.2278848137, -0.0415383584, -0.1210077677, +-0.0724354048, -0.0482025571, 0.1580149098, 0.0583926960, -0.1117559432, +-0.0381725259, 0.1789819529, -0.0148415779, 0.0500966207, -0.1980592117, +-0.1400114013, -0.1746734639, -0.1767850853, -0.2154143864, -0.4144745850, +-0.3405434088, -0.4482790416, -0.6571159536, -0.3546433053, -0.5257081174, +-0.6564372310, -0.5245263017, -0.4758655851, -0.3631316786, -0.3366915389, +-0.3254437415, 0.0006694692, 0.2080422414, 0.0023164951, 0.1124752107, + 0.3494037146, 0.4717023945, 0.5906600432, 0.6048634064, 0.9331979099) + diff --git a/examples/arK/arK.stan b/examples/arK/arK.stan new file mode 100644 index 0000000000..d3177c889c --- /dev/null +++ b/examples/arK/arK.stan @@ -0,0 +1,27 @@ +data { + int K; + int T; + real y[T]; +} + +parameters { + real alpha; + real beta[K]; + real sigma; +} + +model { + alpha ~ normal(0, 10); + beta ~ normal(0, 10); + sigma ~ cauchy(0, 2.5); + + for (t in (K+1):T) { + real mu; + mu = alpha; + + for (k in 1:K) + mu = mu + beta[k] * y[t - k]; + + y[t] ~ normal(mu, sigma); + } +} diff --git a/examples/arK/mpi.0.output.csv b/examples/arK/mpi.0.output.csv new file mode 100644 index 0000000000..9f05983485 --- /dev/null +++ b/examples/arK/mpi.0.output.csv @@ -0,0 +1,1409 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = arK_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 0 (Default) +# data +# file = arK.data.R +# init = 2 (Default) +# random +# seed = 4809463 +# output +# file = mpi.0.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,alpha,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +28.1904,1,0.125,1,1,0,111.864,0.256249,1.03091,0.0919795,-0.187369,-1.12116,1.4515,0.722111 +28.1904,0,14.3855,0,1,1,-24.587,0.256249,1.03091,0.0919795,-0.187369,-1.12116,1.4515,0.722111 +28.1904,0,2.43117,0,1,1,-23.719,0.256249,1.03091,0.0919795,-0.187369,-1.12116,1.4515,0.722111 +28.1904,0,0.239791,0,1,1,-25.7599,0.256249,1.03091,0.0919795,-0.187369,-1.12116,1.4515,0.722111 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+271.99,0.902545,0.901359,2,3,0,-266.424,0.000207408,0.621816,0.560911,-0.00451628,0.0646595,-0.345835,0.149017 +270.753,0.864123,1.06215,2,3,0,-269.437,0.00334254,0.684697,0.423353,0.0296034,0.177477,-0.429298,0.149006 +# num_warmup = 350 +# Adaptation terminated +# Step size = 1.17896 +# Elements of inverse mass matrix: +# 0.00012716, 5.60092e-05, -5.60918e-05, -8.39059e-05, 8.29285e-05, 1.93422e-05, 9.38573e-06 +# 5.60092e-05, 0.00463299, -0.00320271, -0.00230628, 5.61468e-05, 0.00121692, 0.000135069 +# -5.60918e-05, -0.00320271, 0.00652315, -0.00203766, -0.00164821, 0.00033198, -0.000301214 +# -8.39059e-05, -0.00230628, -0.00203766, 0.00855908, -0.00196667, -0.00237346, -0.000119245 +# 8.29285e-05, 5.61468e-05, -0.00164821, -0.00196667, 0.00716597, -0.0037339, 0.000637129 +# 1.93422e-05, 0.00121692, 0.00033198, -0.00237346, -0.0037339, 0.00494552, -0.000388994 +# 9.38573e-06, 0.000135069, -0.000301214, -0.000119245, 0.000637129, -0.000388994, 0.00268108 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+270.776,0.706999,1.17896,2,3,0,-268.191,0.0242242,0.685711,0.428249,0.167055,-0.0317648,-0.327918,0.150082 +# +# Elapsed Time: 0.175404 seconds (Warm-up) +# 0.141061 seconds (Sampling) +# 0.316465 seconds (Total) +# diff --git a/examples/arK/mpi.1.output.csv b/examples/arK/mpi.1.output.csv new file mode 100644 index 0000000000..83505a963d --- /dev/null +++ b/examples/arK/mpi.1.output.csv @@ -0,0 +1,1409 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = arK_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 1 +# data +# file = arK.data.R +# init = 2 (Default) +# random +# seed = 4809463 +# output +# file = mpi.1.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,alpha,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +-279.297,1,0.0625,2,3,0,310.854,0.131107,1.63742,1.705,1.76975,-0.281715,1.28629,2.74101 +-279.297,0,14.3855,0,1,1,281.62,0.131107,1.63742,1.705,1.76975,-0.281715,1.28629,2.74101 +-279.297,0,2.43117,0,1,1,283.279,0.131107,1.63742,1.705,1.76975,-0.281715,1.28629,2.74101 +-279.297,2.0348e-90,0.239791,1,1,0,282.339,0.131107,1.63742,1.705,1.76975,-0.281715,1.28629,2.74101 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-0.00230628, 5.61468e-05, 0.00121692, 0.000135069 +# -5.60918e-05, -0.00320271, 0.00652315, -0.00203766, -0.00164821, 0.00033198, -0.000301214 +# -8.39059e-05, -0.00230628, -0.00203766, 0.00855908, -0.00196667, -0.00237346, -0.000119245 +# 8.29285e-05, 5.61468e-05, -0.00164821, -0.00196667, 0.00716597, -0.0037339, 0.000637129 +# 1.93422e-05, 0.00121692, 0.00033198, -0.00237346, -0.0037339, 0.00494552, -0.000388994 +# 9.38573e-06, 0.000135069, -0.000301214, -0.000119245, 0.000637129, -0.000388994, 0.00268108 +271.571,0.911016,0.507197,3,7,0,-270.688,-0.0145862,0.581194,0.528363,0.123673,-0.0779708,-0.280411,0.150309 +271.339,0.942291,0.507197,3,7,0,-267.29,-0.000155479,0.821054,0.260615,0.145032,0.0145867,-0.323197,0.152921 +267.513,0.874829,0.507197,3,7,0,-264.865,-0.000858808,0.562191,0.728198,-0.0635951,-0.12162,-0.217464,0.151035 +270.076,1,0.507197,3,7,0,-266.208,0.00229937,0.745586,0.26365,0.294976,0.0050572,-0.40622,0.149547 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stan_version_patch = 0 +# model = arK_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 2 +# data +# file = arK.data.R +# init = 2 (Default) +# random +# seed = 4809463 +# output +# file = mpi.2.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) 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-0.00230628, 5.61468e-05, 0.00121692, 0.000135069 +# -5.60918e-05, -0.00320271, 0.00652315, -0.00203766, -0.00164821, 0.00033198, -0.000301214 +# -8.39059e-05, -0.00230628, -0.00203766, 0.00855908, -0.00196667, -0.00237346, -0.000119245 +# 8.29285e-05, 5.61468e-05, -0.00164821, -0.00196667, 0.00716597, -0.0037339, 0.000637129 +# 1.93422e-05, 0.00121692, 0.00033198, -0.00237346, -0.0037339, 0.00494552, -0.000388994 +# 9.38573e-06, 0.000135069, -0.000301214, -0.000119245, 0.000637129, -0.000388994, 0.00268108 +270.975,0.852951,0.885719,2,7,0,-266.972,0.0122201,0.545855,0.535382,0.167242,-0.00556981,-0.345597,0.146194 +271.727,0.903126,0.885719,2,3,0,-267.633,-0.0113251,0.750083,0.474765,0.0374451,-0.032858,-0.310411,0.157226 +264.25,0.369856,0.885719,2,3,0,-262.717,0.0205868,0.567861,0.48079,0.226279,-0.228312,-0.160632,0.168991 +266.613,0.962717,0.885719,2,7,0,-263.419,-0.0164742,0.787976,0.466522,-0.0180225,0.0624471,-0.388248,0.137167 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stan_version_patch = 0 +# model = arK_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 3 +# data +# file = arK.data.R +# init = 2 (Default) +# random +# seed = 4809463 +# output +# file = mpi.3.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) 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-5.60918e-05, -8.39059e-05, 8.29285e-05, 1.93422e-05, 9.38573e-06 +# 5.60092e-05, 0.00463299, -0.00320271, -0.00230628, 5.61468e-05, 0.00121692, 0.000135069 +# -5.60918e-05, -0.00320271, 0.00652315, -0.00203766, -0.00164821, 0.00033198, -0.000301214 +# -8.39059e-05, -0.00230628, -0.00203766, 0.00855908, -0.00196667, -0.00237346, -0.000119245 +# 8.29285e-05, 5.61468e-05, -0.00164821, -0.00196667, 0.00716597, -0.0037339, 0.000637129 +# 1.93422e-05, 0.00121692, 0.00033198, -0.00237346, -0.0037339, 0.00494552, -0.000388994 +# 9.38573e-06, 0.000135069, -0.000301214, -0.000119245, 0.000637129, -0.000388994, 0.00268108 +272.282,0.929306,1.48152,2,3,0,-271.489,0.00966944,0.605204,0.561123,0.0833434,-0.00884757,-0.35553,0.147792 +272.282,0.00614182,1.48152,2,3,0,-265.634,0.00966944,0.605204,0.561123,0.0833434,-0.00884757,-0.35553,0.147792 +271.731,0.715171,1.48152,2,3,0,-271.222,-0.014588,0.766332,0.344141,0.132735,-0.0997517,-0.225443,0.145527 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a/examples/eight_schools/0.output.csv b/examples/eight_schools/0.output.csv new file mode 100644 index 0000000000..2d0177617f --- /dev/null +++ b/examples/eight_schools/0.output.csv @@ -0,0 +1,2062 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = eight_schools_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 0 (Default) +# data +# file = eight_schools.data.R +# init = 2 (Default) +# random +# seed = 1919300 +# output +# file = 0.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,theta_trans.1,theta_trans.2,theta_trans.3,theta_trans.4,theta_trans.5,theta_trans.6,theta_trans.7,theta_trans.8,mu,tau,theta.1,theta.2,theta.3,theta.4,theta.5,theta.6,theta.7,theta.8 +-8.42753,0.219256,2,1,1,0,9.44985,-0.423844,-0.320912,0.938799,-1.78237,0.475004,-0.0989758,-1.30452,0.433566,1.57593,0.205038,1.48903,1.51013,1.76842,1.21048,1.67332,1.55564,1.30845,1.66483 +-8.42753,0,3.4788,0,1,1,11.0315,-0.423844,-0.320912,0.938799,-1.78237,0.475004,-0.0989758,-1.30452,0.433566,1.57593,0.205038,1.48903,1.51013,1.76842,1.21048,1.67332,1.55564,1.30845,1.66483 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1000 +# Adaptation terminated +# Step size = 0.510128 +# Elements of inverse mass matrix: +# 1.0753, 0.0385994, -0.00758803, 0.085206, -0.00496371, -0.0776077, -0.02715, -0.107742, -0.246172, 0.312566 +# 0.0385994, 0.929158, 0.0181461, 0.135956, 0.0378884, 0.046716, 0.240303, 0.140919, -0.345688, 0.132843 +# -0.00758803, 0.0181461, 0.896421, 0.00140679, 0.00807794, 0.00925689, -0.0194489, 0.0267103, 0.078311, 0.0365144 +# 0.085206, 0.135956, 0.00140679, 0.918919, 0.0626324, 0.041473, 0.0561628, 0.0849092, -0.554996, 0.0895351 +# -0.00496371, 0.0378884, 0.00807794, 0.0626324, 0.876621, 0.00488114, 0.0428587, -0.026816, 0.123127, -0.0473851 +# -0.0776077, 0.046716, 0.00925689, 0.041473, 0.00488114, 0.794091, 0.0211857, 0.0100325, -0.34714, -0.0851123 +# -0.02715, 0.240303, -0.0194489, 0.0561628, 0.0428587, 0.0211857, 1.00386, -0.00915677, -0.480429, 0.199269 +# -0.107742, 0.140919, 0.0267103, 0.0849092, -0.026816, 0.0100325, -0.00915677, 0.850676, -0.1112, 0.0485921 +# -0.246172, -0.345688, 0.078311, -0.554996, 0.123127, -0.34714, -0.480429, -0.1112, 12.093, -0.643453 +# 0.312566, 0.132843, 0.0365144, 0.0895351, -0.0473851, -0.0851123, 0.199269, 0.0485921, -0.643453, 1.19229 +-6.18337,1,0.510128,3,7,0,11.259,0.505624,1.22623,-1.59766,0.085992,-0.939735,-0.498847,0.616298,-1.7968,5.43068,3.33975,7.11933,9.52596,0.0948829,5.71787,2.2922,3.76465,7.48896,-0.570186 +-7.63129,0.943204,0.510128,3,7,0,11.3478,0.215409,1.73544,-0.841182,-0.475893,-0.556618,-0.901262,1.322,-1.58989,5.45497,9.95568,7.59951,22.7325,-2.91957,0.717133,-0.0865412,-3.5177,18.6164,-10.3735 +-10.1414,0.601821,0.510128,3,7,0,17.3051,0.936569,-1.03237,0.306981,1.18594,0.592602,0.445442,-0.480317,2.44922,-3.00907,5.54292,2.18225,-8.7314,-1.3075,3.56452,0.275674,-0.540025,-5.67143,10.5667 +-11.4803,0.77838,0.510128,3,7,0,18.1097,0.531146,-0.173233,-0.411666,3.03622,1.23747,1.17465,0.104442,1.1301,-3.47458,3.48597,-1.62302,-4.07846,-4.90963,7.10959,0.839206,0.620229,-3.11049,0.464917 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+-4.1292,0.929286,0.510128,3,7,0,6.30045,0.0357476,1.27151,-0.0192504,-0.515505,0.667857,0.224846,0.419407,0.267057,0.224054,7.56115,0.494347,9.8381,0.0784987,-3.67376,5.27382,1.92415,3.39525,2.24331 +# +# Elapsed Time: 0.05911 seconds (Warm-up) +# 0.050574 seconds (Sampling) +# 0.109684 seconds (Total) +# diff --git a/examples/eight_schools/1.output.csv b/examples/eight_schools/1.output.csv new file mode 100644 index 0000000000..e83615036d --- /dev/null +++ b/examples/eight_schools/1.output.csv @@ -0,0 +1,2062 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = eight_schools_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 1 +# data +# file = eight_schools.data.R +# init = 2 (Default) +# random +# seed = 1919300 +# output +# file = 1.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,theta_trans.1,theta_trans.2,theta_trans.3,theta_trans.4,theta_trans.5,theta_trans.6,theta_trans.7,theta_trans.8,mu,tau,theta.1,theta.2,theta.3,theta.4,theta.5,theta.6,theta.7,theta.8 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0.0929419, 0.301277 +# -0.0413913, 0.822884, -0.0132064, 0.000495225, 0.0865028, 0.00561094, 0.0283311, 0.0425164, -0.522875, 0.103122 +# -0.00671444, -0.0132064, 0.904737, -0.0849131, 0.0021899, -0.153024, -0.0742607, 0.0151047, 0.00591886, -0.105066 +# -0.0362957, 0.000495225, -0.0849131, 1.0095, 0.0593485, 0.018587, 0.061204, 0.00529105, -0.438438, -0.0531458 +# 0.0654194, 0.0865028, 0.0021899, 0.0593485, 0.791825, 0.0287217, 0.0562155, 0.130794, -0.288882, -0.125362 +# -0.0378186, 0.00561094, -0.153024, 0.018587, 0.0287217, 0.900229, 0.165963, 0.0618214, -0.661457, 0.0179059 +# 0.0861725, 0.0283311, -0.0742607, 0.061204, 0.0562155, 0.165963, 0.901192, -0.00350264, -0.56645, 0.290646 +# 0.0471396, 0.0425164, 0.0151047, 0.00529105, 0.130794, 0.0618214, -0.00350264, 1.03951, -0.167339, 0.0980181 +# 0.0929419, -0.522875, 0.00591886, -0.438438, -0.288882, -0.661457, -0.56645, -0.167339, 10.5404, -0.249916 +# 0.301277, 0.103122, -0.105066, -0.0531458, -0.125362, 0.0179059, 0.290646, 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index 0000000000..522195370f --- /dev/null +++ b/examples/eight_schools/2.output.csv @@ -0,0 +1,2062 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = eight_schools_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 2 +# data +# file = eight_schools.data.R +# init = 2 (Default) +# random +# seed = 1919300 +# output +# file = 2.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,theta_trans.1,theta_trans.2,theta_trans.3,theta_trans.4,theta_trans.5,theta_trans.6,theta_trans.7,theta_trans.8,mu,tau,theta.1,theta.2,theta.3,theta.4,theta.5,theta.6,theta.7,theta.8 +-10.5103,6.41621e-36,2,1,1,0,17.0684,0.272625,0.753247,-1.82373,-0.945165,-1.40461,-1.81451,-0.930397,1.16931,1.59339,0.452034,1.71663,1.93388,0.769004,1.16615,0.958462,0.773174,1.17282,2.12196 +-10.5103,2.08286e-14,2.33506,1,2,1,14.3849,0.272625,0.753247,-1.82373,-0.945165,-1.40461,-1.81451,-0.930397,1.16931,1.59339,0.452034,1.71663,1.93388,0.769004,1.16615,0.958462,0.773174,1.17282,2.12196 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+-5.16437,0.966739,0.418695,3,7,0,6.03889,1.14255,1.1058,0.348259,0.659459,0.596357,-0.705955,0.95394,-1.1112,-1.48616,9.68443,9.57881,9.2229,1.88653,4.90033,4.28921,-8.32292,7.75221,-12.2474 +-6.1395,0.094118,0.640934,3,7,0,8.94433,1.08566,0.987112,-0.0414933,0.190349,0.269975,-1.02974,0.894524,-0.210415,-3.83952,4.62796,1.18485,0.728797,-4.03155,-2.95859,-2.59008,-8.60514,0.300304,-4.81331 +-9.78021,0.992396,0.123001,5,31,0,14.8161,-1.25388,0.0575308,1.23745,0.488461,-0.41885,-0.90648,-2.11326,0.632296,11.1096,1.67431,9.01023,11.2059,13.1815,11.9275,10.4083,9.59189,7.57136,12.1683 +# num_warmup = 1000 +# Adaptation terminated +# Step size = 0.494306 +# Elements of inverse mass matrix: +# 0.911171, -0.0607049, -0.0465688, 0.0338597, 0.0175844, 0.117613, -0.044923, -0.0393471, -0.0510183, 0.157063 +# -0.0607049, 0.703345, -0.0616449, 0.117566, -0.0300719, 0.0778028, -0.0648237, -0.013303, -0.381598, -0.00518689 +# -0.0465688, -0.0616449, 0.953992, -0.0198853, -0.0185417, 0.012023, 2.53156e-05, -0.00446863, 0.0649499, -0.100209 +# 0.0338597, 0.117566, -0.0198853, 0.8725, -0.149238, 0.0314348, -0.0358934, -0.106318, -0.182472, 0.0720681 +# 0.0175844, -0.0300719, -0.0185417, -0.149238, 0.830926, 0.00830541, 0.0176779, 0.0386377, -0.0783773, -0.0875905 +# 0.117613, 0.0778028, 0.012023, 0.0314348, 0.00830541, 0.750824, -0.0295116, -0.0576825, -0.154104, -0.037965 +# -0.044923, -0.0648237, 2.53156e-05, -0.0358934, 0.0176779, -0.0295116, 0.998014, -0.0638762, -0.28682, 0.175226 +# -0.0393471, -0.013303, -0.00446863, -0.106318, 0.0386377, -0.0576825, -0.0638762, 0.833232, -0.117024, 0.0346496 +# -0.0510183, -0.381598, 0.0649499, -0.182472, -0.0783773, -0.154104, -0.28682, -0.117024, 8.62715, -0.155198 +# 0.157063, -0.00518689, -0.100209, 0.0720681, -0.0875905, -0.037965, 0.175226, 0.0346496, -0.155198, 1.02932 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+-10.3716,0.947539,0.494306,3,7,0,16.2974,2.7595,-0.0280563,-0.797703,-0.110933,-0.391913,-1.71541,0.0380394,-0.784812,4.30323,0.246511,4.98348,4.29631,4.10659,4.27588,4.20662,3.88036,4.31261,4.10977 +-5.92249,0.933449,0.494306,2,7,0,11.0712,1.90811,0.0554751,-0.548755,0.294485,-0.600482,-0.818967,-0.123837,-0.321247,3.18247,0.725913,4.56759,3.22274,2.78412,3.39624,2.74657,2.58797,3.09258,2.94927 +# +# Elapsed Time: 0.059892 seconds (Warm-up) +# 0.042111 seconds (Sampling) +# 0.102003 seconds (Total) +# diff --git a/examples/eight_schools/3.output.csv b/examples/eight_schools/3.output.csv new file mode 100644 index 0000000000..6a78c23d35 --- /dev/null +++ b/examples/eight_schools/3.output.csv @@ -0,0 +1,2062 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = eight_schools_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 3 +# data +# file = eight_schools.data.R +# init = 2 (Default) +# random +# seed = 1919300 +# output +# file = 3.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) 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0.223815 +# 0.0120286, 0.785284, 0.0511466, -0.103335, 0.1381, -0.01245, 0.0159416, -0.0442474, -0.190094, 0.0386223 +# -0.0730857, 0.0511466, 0.966227, 0.0116896, 0.0344988, -0.0447248, 0.0761577, -0.080562, 0.203116, 0.0589829 +# -0.0644378, -0.103335, 0.0116896, 0.909589, -0.0425752, 0.0825271, -0.00982575, -0.0371987, -0.01814, 0.0647298 +# -0.000736156, 0.1381, 0.0344988, -0.0425752, 0.858154, 0.00814196, 0.00916036, -0.0512609, -0.518586, -0.226248 +# -0.0453344, -0.01245, -0.0447248, 0.0825271, 0.00814196, 0.790442, 0.0119003, 0.0403582, -0.148427, -0.0238845 +# 0.0985513, 0.0159416, 0.0761577, -0.00982575, 0.00916036, 0.0119003, 0.764287, -0.00181016, -0.170948, 0.293067 +# -0.0643188, -0.0442474, -0.080562, -0.0371987, -0.0512609, 0.0403582, -0.00181016, 0.949783, -0.00586603, -0.077446 +# -0.316258, -0.190094, 0.203116, -0.01814, -0.518586, -0.148427, -0.170948, -0.00586603, 9.73183, -0.0660885 +# 0.223815, 0.0386223, 0.0589829, 0.0647298, -0.226248, -0.0238845, 0.293067, 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+-6.21567,0.950942,0.455615,3,7,0,9.20727,1.43295,0.480365,-0.213282,0.3406,-1.66633,0.931762,-0.921297,-0.971161,6.34876,3.89229,11.9262,8.21848,5.51861,7.67448,-0.137068,9.97545,2.7628,2.56872 +-6.01461,0.943716,0.455615,3,7,0,9.72805,-0.486673,-0.524114,0.247695,-0.0118964,1.29761,-0.953293,1.24857,1.11685,2.89094,7.01493,-0.523035,-0.785677,4.62851,2.80749,11.9936,-3.79634,11.6496,10.7256 +-7.26087,0.99251,0.455615,3,7,0,11.3081,0.01209,-0.0812886,-0.00619462,-1.28887,-0.601722,2.18731,0.733854,-1.13098,3.51984,1.31069,3.53569,3.4133,3.51173,1.83053,2.73117,6.38674,4.4817,2.03747 +# +# Elapsed Time: 0.071503 seconds (Warm-up) +# 0.047645 seconds (Sampling) +# 0.119148 seconds (Total) +# diff --git a/examples/eight_schools/eight_schools.data.R b/examples/eight_schools/eight_schools.data.R new file mode 100644 index 0000000000..3161927ec2 --- /dev/null +++ b/examples/eight_schools/eight_schools.data.R @@ -0,0 +1,6 @@ +J <- 8 + +y <- c(28, 8, -3, 7, -1, 1, 18, 12) + +sigma <- c(15, 10, 16, 11, 9, 11, 10, 18) + diff --git a/examples/eight_schools/eight_schools.stan b/examples/eight_schools/eight_schools.stan new file mode 100644 index 0000000000..574aaf54a8 --- /dev/null +++ b/examples/eight_schools/eight_schools.stan @@ -0,0 +1,21 @@ +data { + int J; // number of schools + real y[J]; // estimated treatment + real sigma[J]; // std of estimated effect +} +parameters { + vector[J] theta_trans; // transformation of theta + real mu; // hyper-parameter of mean + real tau; // hyper-parameter of sd +} +transformed parameters{ + vector[J] theta; + // original theta + theta=theta_trans*tau+mu; +} +model { + theta_trans ~ normal (0,1); + y ~ normal(theta , sigma); + mu ~ normal(0, 5); // a non-informative prior + tau ~ cauchy(0, 5); +} diff --git a/examples/eight_schools/mpi.0.output.csv b/examples/eight_schools/mpi.0.output.csv new file mode 100644 index 0000000000..3b4fa2a6a7 --- /dev/null +++ b/examples/eight_schools/mpi.0.output.csv @@ -0,0 +1,1312 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = eight_schools_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 0 (Default) +# data +# file = eight_schools.data.R +# init = 2 (Default) +# random +# seed = 1919300 +# output +# file = mpi.0.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,theta_trans.1,theta_trans.2,theta_trans.3,theta_trans.4,theta_trans.5,theta_trans.6,theta_trans.7,theta_trans.8,mu,tau,theta.1,theta.2,theta.3,theta.4,theta.5,theta.6,theta.7,theta.8 +-8.42753,0.219256,2,1,1,0,9.44985,-0.423844,-0.320912,0.938799,-1.78237,0.475004,-0.0989758,-1.30452,0.433566,1.57593,0.205038,1.48903,1.51013,1.76842,1.21048,1.67332,1.55564,1.30845,1.66483 +-8.42753,0,3.4788,0,1,1,11.0315,-0.423844,-0.320912,0.938799,-1.78237,0.475004,-0.0989758,-1.30452,0.433566,1.57593,0.205038,1.48903,1.51013,1.76842,1.21048,1.67332,1.55564,1.30845,1.66483 +-8.42263,0.972135,0.386022,3,15,0,14.0307,-0.751576,-1.29256,-1.11568,-1.98682,0.203939,0.744799,0.522972,-0.454621,0.401674,1.11189,-0.433994,-1.03551,-0.838837,-1.80745,0.628431,1.22981,0.983159,-0.103814 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+-3.04123,0.989482,0.570861,2,3,0,11.2231,0.986005,-0.16589,-1.16214,-0.210029,-0.0238797,-0.0873383,0.386481,-0.0568467,3.03437,3.55422,6.53885,2.44476,-1.09613,2.28788,2.94949,2.72395,4.408,2.83232 +-6.18242,0.52139,0.770795,2,7,0,10.6186,1.3102,-1.77431,0.56501,0.358949,1.04453,0.483854,0.483155,-0.549214,4.50064,1.92317,7.02039,1.08833,5.58725,5.19096,6.50945,5.43118,5.42983,3.44441 +-3.98236,0.969336,0.506334,3,7,0,9.56332,-0.0313305,-0.747826,-0.17616,-1.08726,-0.0943679,-0.799854,0.818243,0.258512,3.62834,2.13642,3.56141,2.03067,3.25199,1.3055,3.42673,1.91952,5.37645,4.18063 +# num_warmup = 250 +# Adaptation terminated +# Step size = 0.661941 +# Elements of inverse mass matrix: +# 1.05416, -0.0680288, -0.121866, 0.0773934, -0.120263, 0.0472275, -0.0422915, -0.0277853, -0.206269, 0.111112 +# -0.0680288, 0.860114, -0.0823325, 0.0733358, 0.000425762, 0.0928291, -0.0462059, 0.0583813, -0.212215, -0.0239646 +# -0.121866, -0.0823325, 0.954263, -0.0344643, 0.20509, -0.0298683, -0.00806992, 0.0496746, -0.150266, -0.0513325 +# 0.0773934, 0.0733358, -0.0344643, 0.808125, -0.0599192, 0.118228, 0.0698142, 0.0980135, -0.39703, 0.049721 +# -0.120263, 0.000425762, 0.20509, -0.0599192, 0.995048, -0.0129625, -0.0462917, -0.00418801, -0.610478, -0.104846 +# 0.0472275, 0.0928291, -0.0298683, 0.118228, -0.0129625, 0.925832, -0.0464622, -0.00434582, -0.266485, 0.00108557 +# -0.0422915, -0.0462059, -0.00806992, 0.0698142, -0.0462917, -0.0464622, 0.919198, 0.0867474, -0.371015, 0.27856 +# -0.0277853, 0.0583813, 0.0496746, 0.0980135, -0.00418801, -0.00434582, 0.0867474, 1.07377, -0.0820568, 0.0921899 +# -0.206269, -0.212215, -0.150266, -0.39703, -0.610478, -0.266485, -0.371015, -0.0820568, 10.392, -0.293684 +# 0.111112, -0.0239646, -0.0513325, 0.049721, -0.104846, 0.00108557, 0.27856, 0.0921899, -0.293684, 1.19898 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+-3.52589,0.924276,0.661941,3,7,0,7.92402,0.928966,0.95081,-0.739751,-0.27054,0.105816,0.398158,0.0518169,-0.800727,2.54457,7.10266,9.1427,9.29785,-2.70963,0.623015,3.29614,5.37255,2.91261,-3.14272 +# +# Elapsed Time: 0.017833 seconds (Warm-up) +# 0.047429 seconds (Sampling) +# 0.065262 seconds (Total) +# diff --git a/examples/eight_schools/mpi.1.output.csv b/examples/eight_schools/mpi.1.output.csv new file mode 100644 index 0000000000..8da5f3dc9d --- /dev/null +++ b/examples/eight_schools/mpi.1.output.csv @@ -0,0 +1,1312 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = eight_schools_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 1 +# data +# file = eight_schools.data.R +# init = 2 (Default) +# random +# seed = 1919300 +# output +# file = mpi.1.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,theta_trans.1,theta_trans.2,theta_trans.3,theta_trans.4,theta_trans.5,theta_trans.6,theta_trans.7,theta_trans.8,mu,tau,theta.1,theta.2,theta.3,theta.4,theta.5,theta.6,theta.7,theta.8 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+-3.4217,0.998614,0.329532,4,15,0,6.36124,-0.442766,-0.807825,-0.454491,0.424117,-0.594487,-0.331076,1.04262,-0.00583488,6.54345,7.98592,3.00756,0.0922279,2.91392,9.93042,1.79593,3.89951,14.8698,6.49686 +# num_warmup = 250 +# Adaptation terminated +# Step size = 0.451761 +# Elements of inverse mass matrix: +# 1.05416, -0.0680288, -0.121866, 0.0773934, -0.120263, 0.0472275, -0.0422915, -0.0277853, -0.206269, 0.111112 +# -0.0680288, 0.860114, -0.0823325, 0.0733358, 0.000425762, 0.0928291, -0.0462059, 0.0583813, -0.212215, -0.0239646 +# -0.121866, -0.0823325, 0.954263, -0.0344643, 0.20509, -0.0298683, -0.00806992, 0.0496746, -0.150266, -0.0513325 +# 0.0773934, 0.0733358, -0.0344643, 0.808125, -0.0599192, 0.118228, 0.0698142, 0.0980135, -0.39703, 0.049721 +# -0.120263, 0.000425762, 0.20509, -0.0599192, 0.995048, -0.0129625, -0.0462917, -0.00418801, -0.610478, -0.104846 +# 0.0472275, 0.0928291, -0.0298683, 0.118228, -0.0129625, 0.925832, -0.0464622, -0.00434582, -0.266485, 0.00108557 +# 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+-7.75447,0.984725,0.451761,3,7,0,17.4468,-1.70655,-0.302203,-1.14634,-0.909133,0.61405,-0.722232,0.00234554,0.934592,-0.238125,2.20728,-4.00497,-0.905173,-2.76843,-2.24484,1.11726,-1.8323,-0.232948,1.82479 +-6.80936,1,0.451761,3,7,0,11.1192,-1.15011,-0.604077,0.441893,-0.482918,-1.12356,-0.294887,-1.48923,0.726283,2.96823,0.83138,2.01205,2.46601,3.33561,2.56674,2.03412,2.72306,1.73011,3.57204 +-6.84073,0.664608,0.451761,3,7,0,13.1413,1.0504,0.66132,-0.0476922,-1.09907,-0.41093,0.988259,-0.0483437,-0.917937,10.121,9.00307,19.5778,16.0749,9.69163,0.226034,6.42137,19.0184,9.68576,1.85676 +# +# Elapsed Time: 0.017649 seconds (Warm-up) +# 0.050199 seconds (Sampling) +# 0.067848 seconds (Total) +# diff --git a/examples/eight_schools/mpi.2.output.csv b/examples/eight_schools/mpi.2.output.csv new file mode 100644 index 0000000000..e01dd14965 --- /dev/null +++ b/examples/eight_schools/mpi.2.output.csv @@ -0,0 +1,1312 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = eight_schools_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 2 +# data +# file = eight_schools.data.R +# init = 2 (Default) +# random +# seed = 1919300 +# output +# file = mpi.2.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,theta_trans.1,theta_trans.2,theta_trans.3,theta_trans.4,theta_trans.5,theta_trans.6,theta_trans.7,theta_trans.8,mu,tau,theta.1,theta.2,theta.3,theta.4,theta.5,theta.6,theta.7,theta.8 +-10.5103,6.41621e-36,2,1,1,0,17.0684,0.272625,0.753247,-1.82373,-0.945165,-1.40461,-1.81451,-0.930397,1.16931,1.59339,0.452034,1.71663,1.93388,0.769004,1.16615,0.958462,0.773174,1.17282,2.12196 +-10.5103,2.08286e-14,2.33506,1,2,1,14.3849,0.272625,0.753247,-1.82373,-0.945165,-1.40461,-1.81451,-0.930397,1.16931,1.59339,0.452034,1.71663,1.93388,0.769004,1.16615,0.958462,0.773174,1.17282,2.12196 +-6.4328,0.999836,0.230236,4,15,0,14.2742,0.35229,0.283201,1.09666,-0.211518,0.85241,1.42952,-0.183995,0.685338,4.47929,7.8713,7.25227,6.70846,13.1114,2.81437,11.1889,15.7315,3.03101,9.87379 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+-3.82349,0.530521,0.757934,3,7,0,9.92672,0.553572,0.450689,-1.11341,1.00453,0.131426,0.118985,-0.218588,-0.63929,5.0134,2.82052,6.57476,6.28457,1.87301,7.84669,5.38409,5.349,4.39687,3.21027 +-6.62693,0.909093,0.506107,3,7,0,8.70146,0.455027,-0.927925,-0.960576,-0.778268,-0.441933,0.138585,-1.10036,-0.614913,-0.239933,2.97444,1.11352,-2.99999,-3.09711,-2.55484,-1.55443,0.172279,-3.51289,-2.06895 +# num_warmup = 250 +# Adaptation terminated +# Step size = 0.60474 +# Elements of inverse mass matrix: +# 1.05416, -0.0680288, -0.121866, 0.0773934, -0.120263, 0.0472275, -0.0422915, -0.0277853, -0.206269, 0.111112 +# -0.0680288, 0.860114, -0.0823325, 0.0733358, 0.000425762, 0.0928291, -0.0462059, 0.0583813, -0.212215, -0.0239646 +# -0.121866, -0.0823325, 0.954263, -0.0344643, 0.20509, -0.0298683, -0.00806992, 0.0496746, -0.150266, -0.0513325 +# 0.0773934, 0.0733358, -0.0344643, 0.808125, -0.0599192, 0.118228, 0.0698142, 0.0980135, -0.39703, 0.049721 +# -0.120263, 0.000425762, 0.20509, -0.0599192, 0.995048, -0.0129625, -0.0462917, -0.00418801, -0.610478, -0.104846 +# 0.0472275, 0.0928291, -0.0298683, 0.118228, -0.0129625, 0.925832, -0.0464622, -0.00434582, -0.266485, 0.00108557 +# -0.0422915, -0.0462059, -0.00806992, 0.0698142, -0.0462917, -0.0464622, 0.919198, 0.0867474, -0.371015, 0.27856 +# -0.0277853, 0.0583813, 0.0496746, 0.0980135, -0.00418801, -0.00434582, 0.0867474, 1.07377, -0.0820568, 0.0921899 +# -0.206269, -0.212215, -0.150266, -0.39703, -0.610478, -0.266485, -0.371015, -0.0820568, 10.392, -0.293684 +# 0.111112, -0.0239646, -0.0513325, 0.049721, -0.104846, 0.00108557, 0.27856, 0.0921899, -0.293684, 1.19898 +-9.16764,0.820942,0.60474,3,7,0,11.851,-0.0863746,0.373762,0.0992449,0.00895509,0.988132,1.37232,1.54274,1.67534,10.7011,1.12142,10.6042,11.1202,10.8123,10.7111,11.8092,12.24,12.4311,12.5798 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0.017832 seconds (Warm-up) +# 0.048156 seconds (Sampling) +# 0.065988 seconds (Total) +# diff --git a/examples/eight_schools/mpi.3.output.csv b/examples/eight_schools/mpi.3.output.csv new file mode 100644 index 0000000000..a7202d0a82 --- /dev/null +++ b/examples/eight_schools/mpi.3.output.csv @@ -0,0 +1,1312 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = eight_schools_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 3 +# data +# file = eight_schools.data.R +# init = 2 (Default) +# random +# seed = 1919300 +# output +# file = mpi.3.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,theta_trans.1,theta_trans.2,theta_trans.3,theta_trans.4,theta_trans.5,theta_trans.6,theta_trans.7,theta_trans.8,mu,tau,theta.1,theta.2,theta.3,theta.4,theta.5,theta.6,theta.7,theta.8 +-13.4935,1.15791e-11,2,1,1,0,15.8703,-1.41387,1.10682,-1.27528,1.96661,-1.18544,-0.45601,-1.98234,0.710066,-0.677682,0.207149,-0.970562,-0.448406,-0.941855,-0.270301,-0.923244,-0.772144,-1.08832,-0.530593 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Adaptation terminated +# Step size = 0.722496 +# Elements of inverse mass matrix: +# 1.05416, -0.0680288, -0.121866, 0.0773934, -0.120263, 0.0472275, -0.0422915, -0.0277853, -0.206269, 0.111112 +# -0.0680288, 0.860114, -0.0823325, 0.0733358, 0.000425762, 0.0928291, -0.0462059, 0.0583813, -0.212215, -0.0239646 +# -0.121866, -0.0823325, 0.954263, -0.0344643, 0.20509, -0.0298683, -0.00806992, 0.0496746, -0.150266, -0.0513325 +# 0.0773934, 0.0733358, -0.0344643, 0.808125, -0.0599192, 0.118228, 0.0698142, 0.0980135, -0.39703, 0.049721 +# -0.120263, 0.000425762, 0.20509, -0.0599192, 0.995048, -0.0129625, -0.0462917, -0.00418801, -0.610478, -0.104846 +# 0.0472275, 0.0928291, -0.0298683, 0.118228, -0.0129625, 0.925832, -0.0464622, -0.00434582, -0.266485, 0.00108557 +# -0.0422915, -0.0462059, -0.00806992, 0.0698142, -0.0462917, -0.0464622, 0.919198, 0.0867474, -0.371015, 0.27856 +# -0.0277853, 0.0583813, 0.0496746, 0.0980135, -0.00418801, -0.00434582, 0.0867474, 1.07377, -0.0820568, 0.0921899 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0000000000..6975bb76b1 --- /dev/null +++ b/examples/garch-garch11/0.output.csv @@ -0,0 +1,2056 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = garch_garch11_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 0 (Default) +# data +# file = garch-garch11.data.R +# init = 2 (Default) +# random +# seed = 1569824 +# output +# file = 0.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,mu,alpha0,alpha1,beta1 +-392.102,0.333334,0.25,2,3,0,554.476,7.19979,0.0820302,0.0436472,0.954855 +-392.102,0,4.28063,0,1,1,395.459,7.19979,0.0820302,0.0436472,0.954855 +-392.102,1.20001e-13,0.505111,2,3,0,393.754,7.19979,0.0820302,0.0436472,0.954855 +-360.961,1,0.0405813,3,7,0,395.25,6.62201,0.092154,0.0571788,0.941815 +-311.375,0.999513,0.0482795,3,7,0,364.598,5.65795,0.211021,0.0919851,0.90695 +-294.618,1,0.0693973,3,7,0,313.884,4.33911,0.296577,0.194951,0.80289 +-285.134,1,0.111957,2,3,0,295.687,4.75637,0.223319,0.216548,0.781525 +-272.539,0.880741,0.193666,2,3,0,284.525,5.10928,0.488243,0.560331,0.438079 +-273.166,0.0555806,0.24028,2,7,0,274.402,4.97043,0.481915,0.581573,0.416478 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+-268.523,0.883508,0.503245,3,7,0,271.372,5.11749,1.46505,0.501387,0.399351 +-267.872,0.977954,0.543408,2,7,0,272.524,5.14754,0.957696,0.586163,0.368618 +-266.829,0.958937,0.638174,2,7,0,268.743,5.10279,1.42658,0.57116,0.294301 +-270.274,0.557707,0.736655,2,7,0,271.549,5.10541,0.663381,0.539208,0.455426 +-270.384,0.963729,0.59507,3,7,0,271.372,5.15832,0.65774,0.537378,0.455611 +-267.922,0.297269,0.689678,3,7,0,272.184,5.01596,0.745267,0.54288,0.400288 +-267.302,1,0.442398,3,7,0,268.667,4.99353,1.13996,0.461356,0.43225 +-268.7,0.90049,0.529483,3,7,0,269.851,5.072,1.42588,0.766685,0.207918 +-268.073,0.97776,0.580058,2,3,0,269.292,5.04543,1.40901,0.647156,0.309876 +-268.168,0.546189,0.680294,2,3,0,270.284,5.08069,2.46109,0.479039,0.195844 +-268.168,0.0959399,0.544694,3,7,0,275.488,5.08069,2.46109,0.479039,0.195844 +-267.712,0.987233,0.2932,3,15,0,269.256,5.14106,1.08317,0.451882,0.438979 +-269.901,0.961063,0.346817,3,7,0,271.478,4.80834,2.21157,0.607254,0.232971 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+-267.997,0.350778,0.628193,3,7,0,270.626,4.89562,1.53073,0.544743,0.342006 +-267.866,0.999461,0.194825,4,15,0,268.721,5.09609,0.901343,0.574624,0.318165 +-268.636,0.955246,0.334271,3,15,0,270.964,5.19813,1.76643,0.77626,0.149886 +-269.197,0.81968,0.507197,2,7,0,270.289,5.14538,2.51652,0.739084,0.0927353 +-269.633,0.91035,0.53979,3,7,0,272.153,4.8498,0.971374,0.327608,0.461926 +-267.817,0.419949,0.723128,2,7,0,270.547,4.98842,2.34623,0.513612,0.168102 +-268.32,0.989493,0.27892,4,15,0,268.83,5.05482,0.688175,0.52518,0.393735 +-267.754,0.997952,0.456014,3,7,0,269.336,4.87523,1.41052,0.491649,0.368798 +-267.363,0.704756,0.755909,2,3,0,269.367,5.05048,1.96105,0.646171,0.195721 +-267.363,0.113464,0.602095,2,3,0,271.572,5.05048,1.96105,0.646171,0.195721 +-268.383,0.996237,0.112558,4,15,0,268.62,5.07098,2.38658,0.671302,0.157896 +-267.9,0.998024,0.185609,4,15,0,269.404,5.14091,1.13794,0.63624,0.24019 +-269.103,0.953614,0.305221,3,15,0,271.179,5.26049,1.19054,0.559022,0.26032 +-268.762,0.979664,0.447928,3,7,0,271.396,4.81281,0.946459,0.441844,0.432197 +-267.516,0.978995,0.695857,3,7,0,269.502,5.01623,0.844459,0.539173,0.404377 +-267.101,0.406571,1.07283,2,3,0,267.652,4.99742,1.18363,0.602011,0.297118 +# num_warmup = 1000 +# Adaptation terminated +# Step size = 0.410404 +# Elements of inverse mass matrix: +# 0.0162334, 0.000224592, 0.0181361, 0.00498987 +# 0.000224592, 0.162519, 0.0555625, -0.339754 +# 0.0181361, 0.0555625, 0.28909, 0.168839 +# 0.00498987, -0.339754, 0.168839, 2.11691 +-268.712,0.928895,0.410404,3,7,0,269.233,4.84793,1.76315,0.483674,0.349603 +-267.445,1,0.410404,2,3,0,268.704,4.91198,1.42988,0.458824,0.313852 +-269.915,0.508246,0.410404,3,7,0,270.967,5.04049,2.6626,0.563883,0.229303 +-267.799,0.978768,0.410404,2,7,0,269.545,5.00831,1.95551,0.465753,0.197062 +-267.732,0.992798,0.410404,4,15,0,268.695,5.06021,1.01211,0.594943,0.284827 +-267.665,0.85075,0.410404,3,7,0,269.266,5.05398,0.866509,0.488857,0.453873 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+-267.209,0.955911,0.410404,2,3,0,267.879,5.11741,1.32314,0.440601,0.358435 +-268.529,0.745072,0.410404,3,7,0,268.922,5.1449,1.20651,0.426124,0.325138 +-269.544,1,0.410404,3,7,0,270.726,5.25728,0.852414,0.582818,0.384501 +-267.79,0.984172,0.410404,3,7,0,270.437,5.06807,0.988411,0.491091,0.335469 +-268.371,1,0.410404,3,7,0,268.685,5.20514,0.943535,0.564539,0.385334 +-267.4,0.988325,0.410404,3,7,0,269.127,4.94261,1.37146,0.556781,0.261356 +# +# Elapsed Time: 0.204671 seconds (Warm-up) +# 0.184233 seconds (Sampling) +# 0.388904 seconds (Total) +# diff --git a/examples/garch-garch11/1.output.csv b/examples/garch-garch11/1.output.csv new file mode 100644 index 0000000000..392952f473 --- /dev/null +++ b/examples/garch-garch11/1.output.csv @@ -0,0 +1,2056 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = garch_garch11_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 1 +# data +# file = garch-garch11.data.R +# init = 2 (Default) +# random +# seed = 1569824 +# output +# file = 1.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,mu,alpha0,alpha1,beta1 +-578.492,1,0.125,1,1,0,638.224,-1.18342,1.35172,0.219002,0.616366 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+-271.169,0.145367,0.885895,2,3,0,272.992,4.85913,2.90247,0.306629,0.210498 +-268.101,0.968411,0.484725,3,7,0,272.421,4.91004,0.922909,0.555945,0.359631 +-266.747,0.917407,0.567796,2,7,0,269.686,5.01256,1.2536,0.519053,0.319461 +-267.192,0.773613,0.634325,2,3,0,268.048,5.0112,1.06004,0.558766,0.373713 +-267.176,0.983027,0.620571,3,7,0,267.875,5.08068,1.78819,0.560592,0.27073 +-267.791,0.813591,0.736198,3,7,0,268.882,5.07389,2.16839,0.460056,0.248181 +-267.791,0.393646,0.747113,1,3,0,273.862,5.07389,2.16839,0.460056,0.248181 +-267.305,0.87484,0.515541,3,7,0,268.983,5.06143,0.981644,0.596339,0.333763 +-267.222,0.856741,0.553613,2,7,0,270.363,5.14688,1.595,0.589437,0.271392 +-270.413,0.874412,0.584629,2,7,0,270.517,5.32954,2.08278,0.561431,0.12701 +-271.296,0.938295,0.627378,3,7,0,272.931,4.8075,0.782376,0.606294,0.363081 +-269.121,0.95423,0.713652,2,7,0,273.563,5.05316,1.39981,0.595895,0.371334 +-271.029,0.629687,0.823472,2,7,0,272.584,4.9949,2.16601,0.745962,0.225664 +-270.78,0.609757,0.706388,2,3,0,274.013,4.95557,0.860622,0.688069,0.304625 +-269.794,0.898066,0.595228,2,3,0,272.247,5.12969,1.50601,0.519483,0.412046 +-270.459,0.925928,0.652403,2,3,0,271.865,4.97444,0.557875,0.540887,0.450759 +-268.545,0.863393,0.733287,2,3,0,271.869,5.02102,1.02568,0.670128,0.308742 +-269.71,0.666693,0.778469,1,3,0,272.121,5.06859,1.57117,0.718832,0.268091 +-271.253,0.644554,0.691182,2,3,0,272.572,4.8647,1.3985,0.700815,0.291764 +-273.756,0.542826,0.601628,3,11,0,277.821,5.04983,3.33565,0.610491,0.00224226 +-273.66,0.997526,0.4777,3,7,0,274.244,5.11062,2.44257,0.670035,0.00478945 +-273.171,0.51742,0.572706,3,7,0,274.409,5.07808,2.51528,0.71597,0.00597 +-273.767,0.962149,0.444638,4,15,0,274.99,4.99003,3.3194,0.383677,0.00783402 +-272.435,0.935809,0.516147,4,15,0,274.237,4.99559,2.59632,0.600385,0.0125297 +-268.215,0.813809,0.584904,3,15,0,274.378,5.13175,1.25165,0.529028,0.402611 +-267.409,0.992991,0.593636,3,7,0,268.67,5.06117,1.27391,0.679032,0.240935 +-268.007,0.976329,0.707981,2,3,0,268.343,4.99873,1.90719,0.664666,0.130912 +-268.007,0.560191,0.83149,2,3,0,273.545,4.99873,1.90719,0.664666,0.130912 +-267.685,0.986988,0.67162,3,7,0,269.169,5.12651,1.597,0.676487,0.246582 +-268.773,0.935504,0.796152,2,3,0,269.198,5.21551,1.50951,0.633404,0.158069 +-269.735,0.890076,0.900873,2,3,0,271.606,5.12631,1.89601,0.853618,0.0940718 +-268.738,0.155976,0.978464,2,3,0,273.979,5.26144,0.973731,0.543563,0.359393 +-270.624,0.955481,0.55077,3,7,0,271.402,4.71181,1.49969,0.522585,0.366375 +-269.05,0.282154,0.634443,3,7,0,272.592,4.79165,1.33908,0.376298,0.442048 +-270.581,0.948025,0.400365,3,7,0,273.042,4.79645,2.93359,0.431223,0.135644 +-267.446,0.970039,0.458144,2,7,0,271.649,4.98475,1.812,0.444246,0.255837 +-266.996,0.976695,0.534509,3,7,0,269.1,4.97387,1.52144,0.450832,0.336037 +-267.345,0.956656,0.627116,3,7,0,268.365,5.1673,1.65472,0.624809,0.232813 +-266.976,0.719183,0.722535,3,7,0,269.18,5.01229,1.55568,0.459809,0.299223 +-268.738,0.719633,0.673859,2,7,0,268.839,5.09517,1.49289,0.797834,0.1489 +-271.257,0.512891,0.628799,2,3,0,272.469,5.1128,2.98703,0.7987,0.0773811 +-269.493,1,0.48849,2,3,0,271.567,5.09955,2.65735,0.741074,0.100951 +-269.2,0.973953,0.584671,2,7,0,272.269,5.14639,2.3871,0.673714,0.187215 +-267.516,0.94924,0.683592,3,7,0,269.243,4.97097,0.9264,0.414529,0.432815 +-268.919,0.656986,0.781727,2,7,0,269.444,4.88617,0.683798,0.455433,0.489608 +-270.826,0.932859,0.690294,2,3,0,271.556,5.2727,2.85757,0.688735,0.0736964 +-272.447,0.332408,0.777842,3,7,0,274.064,5.33043,2.613,0.597245,0.035779 +-270.265,0.859659,0.515999,3,7,0,274.933,4.8106,1.65304,0.696836,0.249108 +-269.209,0.814278,0.545149,3,7,0,273.28,4.81226,1.84427,0.357017,0.351131 +-268.543,0.873596,0.55333,2,3,0,272.271,4.85068,1.04072,0.376696,0.48948 +-267.782,1,0.591693,3,7,0,269.113,5.08523,2.10181,0.678754,0.128106 +-268.956,0.551081,0.706939,2,3,0,270.33,5.02887,0.59908,0.544111,0.419894 +-269.368,0.957753,0.569367,3,7,0,272.73,5.14864,1.35369,0.810742,0.154696 +-269.05,0.520472,1.31064,2,3,0,270.205,4.9722,1.42513,0.757224,0.161581 +-269.05,0,7.88427,0,1,1,271.603,4.9722,1.42513,0.757224,0.161581 +-272.111,0.505786,1.02904,2,3,0,274.024,4.93422,0.628513,0.238286,0.639535 +-271.379,0.978582,0.337058,3,7,0,274.162,5.03369,2.45652,0.88245,0.0777166 +-271.916,0.879096,0.431002,2,7,0,275.843,5.17134,2.06537,0.710095,0.0296393 +-272.118,0.693731,0.470312,3,15,0,276.043,4.89332,2.81394,0.587214,0.0208858 +-271.544,0.749588,0.310518,3,15,0,278.147,5.02899,0.916867,0.747119,0.248931 +-270.351,0.96535,0.249448,3,11,0,275.266,4.85161,0.710159,0.470887,0.509007 +-268.882,0.987656,0.403691,3,7,0,271.992,4.9465,2.61086,0.616059,0.103859 +-269.456,0.951511,0.717964,2,3,0,271.136,5.23721,0.876768,0.650714,0.314445 +-269.456,0.220763,1.1546,1,3,0,271.575,5.23721,0.876768,0.650714,0.314445 +-269.247,0.992127,0.185793,4,15,0,272.686,4.88376,1.90326,0.625247,0.131589 +-269.547,0.941981,0.344636,2,3,0,270.482,4.90946,1.66771,0.619712,0.139513 +-269.807,0.967682,0.546602,3,7,0,270.911,5.21044,1.90791,0.405911,0.212046 +-269.807,0.150506,0.93824,2,3,0,270.178,5.21044,1.90791,0.405911,0.212046 +-269.088,1,0.127517,4,15,0,270.376,5.24349,1.87348,0.426075,0.280239 +-267.745,0.99542,0.243648,4,15,0,270.487,5.03626,1.7837,0.719642,0.154046 +-269.127,0.837438,0.455802,3,7,0,270.233,5.07692,1.4787,0.307943,0.458809 +-270.028,0.87052,0.524042,3,7,0,271.057,4.9785,1.57423,0.818224,0.120267 +-268.826,1,0.664743,2,3,0,270.776,5.00728,1.30359,0.761969,0.195834 +-268.826,2.19721e-13,1.23669,1,1,0,272.945,5.00728,1.30359,0.761969,0.195834 +-266.8,0.998,0.118478,5,31,0,270.163,5.06156,1.38779,0.469996,0.345772 +-267.075,0.998051,0.220291,4,15,0,267.228,5.13534,1.4548,0.628184,0.236438 +-269.399,0.898449,0.4056,2,7,0,270.181,5.11522,1.15451,0.780349,0.191436 +-268.127,0.286678,0.554874,3,7,0,271.714,4.99633,0.984075,0.648794,0.307668 +-267.738,0.99969,0.131514,4,15,0,268.808,5.05557,1.13461,0.629021,0.245363 +-268.34,0.96824,0.240812,2,7,0,272.844,5.0382,0.732225,0.470705,0.404341 +-269.078,0.987362,0.399616,4,15,0,269.595,4.98583,0.686082,0.583605,0.365824 +-269.078,0.235667,0.69353,2,3,0,271.906,4.98583,0.686082,0.583605,0.365824 +-266.984,1,0.149604,4,15,0,269.339,5.04386,1.05615,0.444952,0.423015 +-267.137,0.977992,0.268535,4,15,0,268.067,5.14283,1.70581,0.552564,0.229801 +-267.999,0.97124,0.449679,3,7,0,268.533,5.18157,1.84274,0.687512,0.136642 +-269.739,0.426125,0.733207,3,7,0,270.36,4.74897,1.32187,0.449958,0.425178 +-268.622,0.998311,0.276404,3,15,0,271.261,5.23415,1.21295,0.623569,0.230717 +-268.156,0.972031,0.48225,3,7,0,269.956,5.0227,2.12562,0.659482,0.207206 +-271.249,0.283277,0.778246,2,7,0,272.683,5.17601,0.708636,0.578694,0.418653 +-272.135,0.992797,0.206701,3,7,0,272.437,5.19002,0.682529,0.470787,0.524576 +-270.244,1,0.351629,2,3,0,272.295,5.20343,0.901422,0.602673,0.389731 +-269.253,0.872767,0.604318,3,7,0,271.958,4.91567,0.889335,0.592338,0.390139 +-271.013,0.875349,0.744695,2,3,0,271.395,4.8298,0.931884,0.441139,0.527955 +-269.351,0.53929,0.920712,2,3,0,272.753,4.91956,1.38208,0.740697,0.227032 +-269.826,0.591287,0.487956,2,7,0,271.197,5.03076,1.92422,0.847155,0.111951 +-267.078,0.993811,0.297124,4,15,0,271.978,5.14898,1.41015,0.550657,0.306431 +-267.559,0.960057,0.493348,3,7,0,268.054,4.98101,1.70261,0.679759,0.191883 +-268.455,0.687181,0.748415,2,7,0,269.762,5.00953,2.57149,0.481326,0.203916 +-267.482,0.884179,0.580009,3,7,0,269.516,5.04405,0.895581,0.556604,0.345874 +-267.387,0.947814,0.726897,3,7,0,268.074,4.98931,1.93047,0.48162,0.283808 +-267.387,0.0822754,1.05825,2,3,0,268.798,4.98931,1.93047,0.48162,0.283808 +-267.269,0.996425,0.193817,5,31,0,268.213,5.1268,1.83339,0.559261,0.192592 +-268.872,0.977803,0.317826,4,15,0,269.406,5.04996,2.70824,0.649557,0.118624 +# num_warmup = 1000 +# Adaptation terminated +# Step size = 0.448336 +# Elements of inverse mass matrix: +# 0.0143095, 0.0026371, 0.0166115, -0.00158449 +# 0.0026371, 0.144817, 0.0465173, -0.377657 +# 0.0166115, 0.0465173, 0.32691, 0.129201 +# -0.00158449, -0.377657, 0.129201, 2.01814 +-268.213,1,0.448336,3,7,0,270.034,4.88608,0.811414,0.46472,0.448348 +-268.51,0.967911,0.448336,3,15,0,269.022,5.2296,1.79714,0.64989,0.236121 +-266.994,0.992776,0.448336,3,7,0,268.745,5.02403,1.81931,0.552978,0.210087 +-268.125,0.941513,0.448336,2,7,0,269.256,5.06783,1.2675,0.361457,0.466434 +-268.418,0.996642,0.448336,3,7,0,268.843,5.04941,1.46729,0.771896,0.166344 +-267.982,1,0.448336,3,7,0,268.787,5.00227,1.80051,0.730827,0.173031 +-270.201,0.922511,0.448336,3,7,0,271.326,4.83075,1.68131,0.324103,0.457519 +-267.901,0.979195,0.448336,3,7,0,270.96,5.12173,1.36418,0.732123,0.195061 +-267.495,0.987191,0.448336,3,7,0,268.634,5.10521,1.73703,0.661626,0.233263 +-267.206,0.947455,0.448336,3,7,0,268.797,4.96305,1.27694,0.40803,0.405987 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+-268.353,0.000688706,0.448336,2,3,0,272.171,4.9202,0.942782,0.34089,0.503123 +-267.475,0.869918,0.448336,3,7,0,270.284,5.00682,1.7467,0.487169,0.331191 +# +# Elapsed Time: 0.210553 seconds (Warm-up) +# 0.203082 seconds (Sampling) +# 0.413635 seconds (Total) +# diff --git a/examples/garch-garch11/2.output.csv b/examples/garch-garch11/2.output.csv new file mode 100644 index 0000000000..960c69dc29 --- /dev/null +++ b/examples/garch-garch11/2.output.csv @@ -0,0 +1,2056 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = garch_garch11_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 2 +# data +# file = garch-garch11.data.R +# init = 2 (Default) +# random +# seed = 1569824 +# output +# file = 2.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,mu,alpha0,alpha1,beta1 +-426.132,1,0.25,2,3,0,505.992,1.69384,17.8206,0.486779,0.301825 +-426.132,0,14.3855,0,1,1,426.274,1.69384,17.8206,0.486779,0.301825 +-426.132,0,2.43117,0,1,1,426.669,1.69384,17.8206,0.486779,0.301825 +-372.485,1,0.239791,1,3,0,429.016,2.38191,7.46724,0.389119,0.241312 +-305.819,1,0.324332,1,1,0,369.536,4.87164,9.3944,0.416185,0.184202 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+-267.946,0.958666,0.482988,3,7,0,271.813,4.98579,1.7253,0.438251,0.238628 +-269.62,0.993939,0.755465,2,7,0,270.896,4.94125,1.37828,0.775045,0.178424 +-268.746,0.910119,1.28994,2,3,0,269.613,5.06963,1.57152,0.765501,0.207442 +-268.746,0.0923697,1.74536,2,3,0,270.662,5.06963,1.57152,0.765501,0.207442 +-269.29,0.992809,0.269028,4,15,0,270.049,5.10987,1.46235,0.693086,0.289646 +-270.722,0.972649,0.455872,3,7,0,271.712,4.99879,1.50845,0.759877,0.0978748 +-269.76,0.880496,0.726811,2,3,0,272.46,4.91076,1.58437,0.498059,0.414631 +-270.95,0.550814,0.906223,2,7,0,272.215,5.2281,2.74839,0.690147,0.0350922 +-273.45,0.899854,0.482837,3,7,0,273.765,5.19647,1.84534,0.549513,0.0550887 +-271.776,0.861836,0.632261,3,7,0,273.591,5.22467,3.12818,0.557784,0.023564 +-270.606,0.517649,0.748923,2,3,0,272.074,5.18813,2.752,0.619293,0.0347726 +-267.628,0.982715,0.372835,3,7,0,271.915,5.14261,1.67883,0.640911,0.160261 +-268.588,0.841711,0.597675,3,7,0,269.471,5.02925,0.628588,0.473746,0.489297 +-268.468,0.901104,0.671237,3,7,0,270.394,5.14218,0.862282,0.466913,0.478232 +-267.634,0.48229,0.870781,2,3,0,269.986,5.1804,1.82259,0.654733,0.195452 +-270.496,0.902111,0.405159,3,7,0,272.493,5.36307,1.35723,0.526428,0.34382 +-269.034,0.968329,0.526767,2,7,0,272.579,5.22051,1.6318,0.689789,0.256077 +-268.643,1,0.800164,2,3,0,270.071,5.27107,1.5378,0.668596,0.226391 +-268.602,1,1.30343,2,3,0,268.957,4.82026,1.03524,0.499039,0.382759 +-268.602,7.79877e-05,2.10916,1,3,1,270.83,4.82026,1.03524,0.499039,0.382759 +# num_warmup = 1000 +# Adaptation terminated +# Step size = 0.632247 +# Elements of inverse mass matrix: +# 0.0156936, 0.00132014, 0.0169857, 0.0097108 +# 0.00132014, 0.161038, 0.0640309, -0.373145 +# 0.0169857, 0.0640309, 0.256275, -0.00829502 +# 0.0097108, -0.373145, -0.00829502, 1.57741 +-269.259,0.346938,0.632247,3,7,0,271.67,5.10861,1.50832,0.73616,0.247948 +-268.862,0.917258,0.632247,3,7,0,270.253,4.91118,1.15676,0.608102,0.363224 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0000000000..f59b5798e3 --- /dev/null +++ b/examples/garch-garch11/3.output.csv @@ -0,0 +1,2056 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = garch_garch11_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 3 +# data +# file = garch-garch11.data.R +# init = 2 (Default) +# random +# seed = 1569824 +# output +# file = 3.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,mu,alpha0,alpha1,beta1 +-330.786,1,0.25,2,3,0,474.819,5.86936,12.8756,0.802832,0.0789824 +-330.786,0,14.3855,0,1,1,331.721,5.86936,12.8756,0.802832,0.0789824 +-330.786,0,2.43117,0,1,1,331.339,5.86936,12.8756,0.802832,0.0789824 +-281.992,1,0.239791,1,1,0,317.012,5.60496,3.60589,0.837644,0.0602237 +-281.992,6.51213e-80,0.324332,1,1,0,284.916,5.60496,3.60589,0.837644,0.0602237 +-280.377,0.998923,0.0257257,3,7,0,282.862,5.5614,3.50052,0.833948,0.0639916 +-271.382,1,0.0402734,4,15,0,281.25,5.27941,2.47737,0.836196,0.0670997 +-271.523,0.997872,0.0684943,3,7,0,271.789,5.29212,2.48726,0.834177,0.0695638 +-270.419,0.99356,0.12157,4,15,0,271.538,4.96826,2.39276,0.818316,0.074334 +-268.978,0.488623,0.219293,3,15,0,271.448,5.08367,2.17577,0.746151,0.0770908 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+-268.942,0.965197,0.302142,3,7,0,273.294,4.97454,0.726552,0.595059,0.362071 +-269.147,0.981358,0.460536,3,7,0,270.294,4.92305,0.847465,0.354154,0.457901 +-269.758,0.873142,0.725317,3,7,0,272.061,5.1676,2.51781,0.767087,0.117166 +-269.727,1,0.878134,2,3,0,271.139,5.30753,1.66329,0.748979,0.140992 +# num_warmup = 1000 +# Adaptation terminated +# Step size = 0.520801 +# Elements of inverse mass matrix: +# 0.0151895, 0.00440458, 0.0137062, -0.0106186 +# 0.00440458, 0.166459, 0.0904895, -0.37013 +# 0.0137062, 0.0904895, 0.304293, -0.0333509 +# -0.0106186, -0.37013, -0.0333509, 1.51195 +-266.843,0.989831,0.520801,2,7,0,269.796,5.01796,1.54332,0.567182,0.290563 +-267.594,0.856249,0.520801,2,7,0,270.109,5.14174,1.49059,0.532462,0.228664 +-268.45,0.844104,0.520801,3,7,0,269.388,4.99575,1.20292,0.689693,0.284082 +-267.996,1,0.520801,2,3,0,268.528,4.99113,1.25414,0.665358,0.295112 +-268.665,0.915301,0.520801,2,7,0,269.49,4.9287,0.828876,0.581229,0.385706 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+-268.251,0.821666,0.520801,2,3,0,268.979,5.0032,0.754224,0.399593,0.522665 +-268.205,0.949367,0.520801,3,7,0,270.14,5.22701,1.76072,0.675128,0.155338 +-268.363,0.881006,0.520801,3,7,0,270.511,4.94406,2.08534,0.669579,0.129948 +-269.187,0.891933,0.520801,3,7,0,271.074,4.97036,1.99728,0.775196,0.107185 +-270.528,0.954774,0.520801,3,7,0,271.615,5.18076,1.02353,0.480442,0.490084 +-272.045,0.956605,0.520801,3,7,0,272.612,5.00468,2.25109,0.809317,0.0272207 +-268.875,0.945382,0.520801,3,15,0,272.958,5.19993,1.07731,0.606327,0.364539 +# +# Elapsed Time: 0.239351 seconds (Warm-up) +# 0.159932 seconds (Sampling) +# 0.399283 seconds (Total) +# diff --git a/examples/garch-garch11/garch-garch11.data.R b/examples/garch-garch11/garch-garch11.data.R new file mode 100644 index 0000000000..e6662cb0df --- /dev/null +++ b/examples/garch-garch11/garch-garch11.data.R @@ -0,0 +1,37 @@ +T <- 200 +sigma1 <- 0.5 +y <- c( + 4.9376697, 4.8899168, 5.0254610, 4.3556765, 3.8357394, 6.4251189, + 6.2174959, 5.3789445, 6.1202710, 5.1143114, 7.6245731, -1.8588047, + 5.5093409, 6.4493257, 5.1634192, 3.4463904, 4.1698488, 4.1064708, + 4.3614838, 5.9580466, 4.0459563, 3.1268747, 3.0014272, 7.2568532, + 0.6181061, -0.1529171, 9.1520129, 4.2929169, 8.4797655, 3.4712109, +-0.7844602, 6.3643689, 7.3924605, 7.4482162, 7.9462958, 7.4520089, + 4.9160684, 7.0783740, 2.2755717, 4.3338510, 5.3356670, 7.7133457, + 3.8465556, 6.5227739, 3.8073106, 5.5854836, 4.0171510, 3.9905454, + 5.3564230, 5.6389753, 5.8895307, 6.0430888, 7.0166372, 5.2398473, + 7.5704829, 7.1371788, 5.0647421, 3.9293894, 3.4554177, 4.3275448, + 8.2122458, 5.4182330, 4.7841770, 3.9840486, 8.2691524, 3.3376053, + 2.0656949, 1.5275422, 1.8313308, 3.4272586, 10.6728548, 9.1516989, + 5.0237735, 9.3370065, 6.2413672, 6.0495085, 5.1750646, 3.5839200, + 2.5954829, 4.8390738, 3.9602637, 5.8275888, 4.2354627, 7.2289368, + 2.6012532, 4.6906417, 1.9171748, 4.6100141, 5.4795416, 5.1599669, + 6.1819383, 4.3444092, 4.4134581, 6.6869847, 3.3489950, 6.8327026, + 4.1952444, 6.7873446, 3.3809638, 6.9186328, 3.6888826, 6.2622409, + 3.4474512, 0.5621525, 12.0983927, -3.9476306, -3.2151898, 8.9190162, + 6.9925151, 8.6113043, 0.7972950, 0.7407605, 6.6504390, -1.0102533, + 6.0100541, 1.0596830, 6.8292719, 4.1636762, 5.1217723, 5.3588360, + 2.9456964, 3.0978778, 4.2588637, 7.3676196, 2.1469861, 7.3753851, + 4.8272418, 4.5120439, 5.7304457, 4.4193964, 2.7559061, 4.3644689, + 7.1601115, 8.2984161, 2.8166543, 3.9179671, 9.7952480, -4.7242886, + 5.4548679, 6.5446901, 6.5973368, 6.2416000, 3.0396850, 1.2093547, + 5.2636842, 8.6437868, 7.4910598, 6.4736415, 4.5251063, 6.7226653, + 4.9341330, 4.1566114, 4.5100764, 6.2950699, 3.1982652, 5.0967501, + 3.2661672, 5.5375760, 6.2441927, 7.2051307, 3.0704887, 2.7454787, + 0.9819569, 5.2894448, 3.8637890, 3.2133096, 5.9141655, 7.2122398, + 5.7235900, 6.8712588, 2.7826501, 3.9139987, 5.8714783, 4.8225299, + 6.4460635, 4.9013858, 4.7609188, 6.5644727, 2.6157804, 7.2306003, + 4.3068921, 3.9418201, 8.9272450, 3.4283380, 1.1672301, 0.8543514, +12.1460656, -6.3507524, 7.7055931, 4.5136553, 4.9229184, 6.4621882, + 0.2856913, 3.6447997, 6.2438314, 7.6303149, 8.8403182, 6.9152914, + 4.1049014, 5.2848041) diff --git a/examples/garch-garch11/garch-garch11.stan b/examples/garch-garch11/garch-garch11.stan new file mode 100644 index 0000000000..526f4bd32f --- /dev/null +++ b/examples/garch-garch11/garch-garch11.stan @@ -0,0 +1,24 @@ +/* stan_code(posterior("garch-garch11", pdb = pd)) */ +data { + int T; + real y[T]; + real sigma1; +} + +parameters { + real mu; + real alpha0; + real alpha1; + real beta1; +} + +model { + real sigma[T]; + sigma[1] = sigma1; + for (t in 2:T) + sigma[t] = sqrt( alpha0 + + alpha1 * square(y[t - 1] - mu) + + beta1 * square(sigma[t - 1])); + + y ~ normal(mu, sigma); +} diff --git a/examples/garch-garch11/mpi.0.output.csv b/examples/garch-garch11/mpi.0.output.csv new file mode 100644 index 0000000000..02956f67d1 --- /dev/null +++ b/examples/garch-garch11/mpi.0.output.csv @@ -0,0 +1,1406 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = garch_garch11_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 0 (Default) +# data +# file = garch-garch11.data.R +# init = 2 (Default) +# random +# seed = 1569824 +# output +# file = mpi.0.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,mu,alpha0,alpha1,beta1 +-392.102,0.333334,0.25,2,3,0,554.476,7.19979,0.0820302,0.0436472,0.954855 +-392.102,0,4.28063,0,1,1,395.459,7.19979,0.0820302,0.0436472,0.954855 +-392.102,1.20001e-13,0.505111,2,3,0,393.754,7.19979,0.0820302,0.0436472,0.954855 +-360.961,1,0.0405813,3,7,0,395.25,6.62201,0.092154,0.0571788,0.941815 +-311.375,0.999513,0.0482795,3,7,0,364.598,5.65795,0.211021,0.0919851,0.90695 +-294.618,1,0.0693973,3,7,0,313.884,4.33911,0.296577,0.194951,0.80289 +-285.134,1,0.111957,2,3,0,295.687,4.75637,0.223319,0.216548,0.781525 +-272.539,0.880741,0.193666,2,3,0,284.525,5.10928,0.488243,0.560331,0.438079 +-273.166,0.0555806,0.24028,2,7,0,274.402,4.97043,0.481915,0.581573,0.416478 +-271.005,0.999992,0.0224879,6,95,0,273.891,5.18701,1.187,0.697271,0.299791 +-267.936,0.999849,0.0419695,6,127,0,272.596,5.11624,0.790505,0.419357,0.467235 +-270.148,0.999949,0.0793934,5,63,0,270.554,5.02262,1.1518,0.735895,0.258641 +-269.074,0.633529,0.151206,4,31,0,273.783,5.19091,0.901519,0.414669,0.403435 +-267.615,0.9981,0.0914001,4,15,0,270.152,5.13632,1.45015,0.594414,0.202468 +-270.182,0.412295,0.17394,5,31,0,271.722,4.84225,0.992351,0.637689,0.287427 +-268.026,0.992906,0.0536777,3,7,0,271.3,5.20168,1.00616,0.600762,0.322886 +-267.973,0.999391,0.100762,4,31,0,269.459,5.1222,1.36865,0.71949,0.178653 +-269.379,0.575529,0.191667,2,7,0,272.231,5.05892,1.31278,0.704881,0.145974 +-270.208,0.592029,0.100102,4,31,0,274.621,5.33463,1.15229,0.450079,0.403338 +-267.844,0.994938,0.055587,4,15,0,272.58,4.96895,0.863891,0.393132,0.456019 +-267.708,0.942812,0.103734,4,31,0,270.941,5.14844,1.34325,0.433111,0.400487 +-266.824,0.988638,0.16439,3,11,0,267.806,5.08074,1.53201,0.568599,0.240955 +-266.824,0.0708432,0.295882,3,7,0,268.232,5.08074,1.53201,0.568599,0.240955 +-267.017,0.990482,0.0366193,5,47,0,269.254,5.1115,1.46001,0.555868,0.245843 +-268.354,0.977207,0.0665122,3,15,0,268.802,5.07118,1.11615,0.555819,0.253078 +-267.458,0.993458,0.11518,2,7,0,269.407,5.07309,1.2719,0.475766,0.297434 +-268.153,0.148069,0.206971,3,9,0,271.146,5.22674,1.97007,0.60039,0.166865 +-268.151,0.999584,0.0342748,4,31,0,269.084,4.98533,1.78744,0.56895,0.153764 +-267.393,0.999925,0.0626901,4,31,0,268.566,5.0351,2.09947,0.494629,0.233914 +-267.556,0.961373,0.113624,3,7,0,268.322,5.0694,1.92943,0.501236,0.289572 +-266.969,0.956253,0.183487,3,11,0,268.37,4.95978,1.27151,0.470917,0.344886 +-266.969,0.00302135,0.289907,2,3,0,270.956,4.95978,1.27151,0.470917,0.344886 +-268.198,0.984762,0.0348727,3,15,0,270.651,5.02556,1.71923,0.430761,0.384449 +-268.124,0.995956,0.0598158,3,7,0,269.096,4.89376,1.63846,0.407249,0.386135 +-267.554,0.998441,0.104768,4,31,0,268.858,5.02373,0.894358,0.439113,0.407965 +-267.554,6.49296e-05,0.183049,2,3,0,277.296,5.02373,0.894358,0.439113,0.407965 +-269.101,0.992589,0.0234394,5,31,0,269.479,4.7858,1.47386,0.399821,0.415783 +-268.725,0.997459,0.0404478,3,11,0,269.869,5.24319,1.12185,0.440947,0.37642 +-266.833,0.999601,0.0700745,4,23,0,269.947,5.03185,1.1461,0.529134,0.326634 +-267.746,0.833759,0.121032,3,11,0,268.358,5.14853,1.21923,0.448366,0.420986 +-270.046,0.987875,0.136269,4,15,0,271.053,4.91602,1.73546,0.734936,0.239939 +-268.214,0.540291,0.225496,4,15,0,270.771,4.99244,0.894974,0.62462,0.319969 +-269.043,1,0.121364,4,15,0,270.366,5.11075,0.758186,0.344305,0.509413 +-268.195,0.947606,0.205554,3,7,0,270.012,5.0671,0.69903,0.411961,0.476633 +-268.195,0.0450815,0.303749,2,7,0,269.033,5.0671,0.69903,0.411961,0.476633 +-266.949,0.999022,0.0493756,5,63,0,269.535,5.07224,1.82871,0.563793,0.235353 +-267.277,0.99221,0.0829915,4,23,0,267.802,5.01325,1.44554,0.461245,0.287505 +-266.925,0.908483,0.136219,2,7,0,268.587,5.0414,1.48968,0.537692,0.249589 +-266.925,0.314535,0.181785,2,7,0,269.138,5.0414,1.48968,0.537692,0.249589 +-267.691,0.987529,0.0590259,5,47,0,268.377,5.15897,1.20635,0.655404,0.283373 +-268.863,0.924364,0.0950391,3,11,0,269.69,5.19832,1.53569,0.743898,0.219423 +-268.683,0.991949,0.131136,3,15,0,270.896,5.00089,1.47731,0.70391,0.267947 +-268.635,0.840518,0.210829,3,15,0,269.955,4.99437,1.56904,0.718239,0.246889 +-268.964,0.149587,0.237366,3,7,0,269.959,5.00415,1.44054,0.775985,0.193769 +-267.869,0.978602,0.0545909,6,95,0,271.56,5.20641,1.56187,0.646705,0.248358 +-270.214,0.943036,0.0848001,5,31,0,270.793,5.21447,2.68799,0.399163,0.192449 +-268.406,0.955755,0.120833,5,31,0,272.153,5.19061,1.28961,0.677331,0.189561 +-267.341,0.805748,0.176386,3,15,0,269.599,5.00856,1.36619,0.45127,0.405826 +-269.418,0.9177,0.183128,3,7,0,269.497,4.91668,0.975485,0.321007,0.456224 +-270.226,0.276641,0.243805,2,3,0,271.79,4.92715,0.807931,0.353256,0.440953 +-268.052,1,0.078278,4,23,0,271.688,5.00718,1.55149,0.653136,0.289145 +-268.387,0.879745,0.125074,3,15,0,271.352,4.92874,1.44836,0.37507,0.447808 +-268.016,0.935528,0.152767,3,7,0,269.373,5.15829,0.955568,0.58242,0.305368 +-267.084,0.513267,0.210142,2,3,0,268.632,5.02595,1.43482,0.54459,0.340476 +-267.935,0.719744,0.115572,3,15,0,270.493,4.8583,1.44483,0.537456,0.283038 +-267.079,0.98975,0.0997407,3,15,0,268.441,4.97595,1.75202,0.544145,0.273103 +-268.81,0.831202,0.15355,4,19,0,269.357,5.24959,0.944937,0.59735,0.332706 +-267.329,0.899391,0.167921,3,11,0,269.131,4.93166,1.13791,0.544134,0.363621 +-267.995,0.544579,0.211885,3,15,0,270.967,5.09537,1.38562,0.36164,0.42014 +-267.872,0.961446,0.126446,4,31,0,270.213,5.00053,1.3837,0.635737,0.312807 +-267.974,0.99965,0.181449,2,3,0,268.052,5.06237,1.41839,0.633174,0.317038 +-267.262,0.341555,0.280807,2,7,0,268.821,5.08337,1.22042,0.649373,0.280514 +-267.233,0.988619,0.110795,4,15,0,267.628,5.03069,0.99833,0.578572,0.356802 +-267.099,0.973173,0.167247,3,7,0,267.672,5.00807,0.982735,0.496037,0.417293 +-267.099,0.0602119,0.243537,2,5,0,267.532,5.00807,0.982735,0.496037,0.417293 +-267.667,0.993624,0.0549697,5,47,0,268.492,5.04587,1.01078,0.420282,0.388254 +-270.551,0.93511,0.0835687,4,15,0,271.874,4.98647,2.6788,0.692082,0.183491 +-270.596,0.970793,0.112415,2,7,0,271.749,4.86109,2.48543,0.710988,0.169853 +-270.542,0.892423,0.161952,3,15,0,271.964,5.08957,2.63334,0.72005,0.175765 +-271.208,0.972309,0.198776,2,3,0,271.745,5.14674,1.10137,0.735786,0.140336 +-271.208,0.317978,0.28536,1,3,0,274.76,5.14674,1.10137,0.735786,0.140336 +-268.298,0.776938,0.111885,2,3,0,272.959,5.23498,1.79492,0.692947,0.159349 +-267.105,0.985005,0.109241,3,11,0,268.984,5.13227,1.6777,0.539027,0.27386 +-268.676,0.821883,0.160361,4,23,0,269.657,4.91914,0.752766,0.505418,0.395961 +-268.007,0.974642,0.170632,3,11,0,271.97,5.15692,1.12556,0.678308,0.272616 +-268.007,0.141908,0.244064,3,7,0,269.198,5.15692,1.12556,0.678308,0.272616 +-268.483,0.996654,0.0696246,5,39,0,270.857,5.06212,2.6594,0.572473,0.150209 +-268.854,0.872731,0.103962,3,7,0,272.598,5.16513,2.39337,0.698521,0.0870413 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+-268.568,0.992898,0.297367,4,15,0,270.531,4.98939,0.919696,0.654096,0.309148 +-269.031,0.982122,0.408579,3,7,0,269.709,5.15356,1.67755,0.400296,0.256243 +-269.284,1,0.550709,3,7,0,270.541,4.95125,1.89861,0.636644,0.288317 +-268.535,0.55285,0.762201,2,3,0,270.696,4.91279,1.53758,0.47588,0.401758 +-270.088,0.83923,0.51881,2,3,0,272.263,4.93258,2.64388,0.596547,0.216765 +-267.244,1,0.556144,2,3,0,269.968,4.9638,1.75649,0.449202,0.296374 +-267.501,0.972925,0.767333,3,7,0,268.018,4.88094,1.24039,0.458666,0.381869 +-267.681,0.457164,1.01269,2,3,0,268.932,5.12189,1.12091,0.662161,0.255122 +-267.014,1,0.595788,3,7,0,267.921,5.02891,1.79918,0.490478,0.277995 +-267.737,0.805753,0.819401,2,3,0,268.868,5.11839,0.884757,0.578794,0.334992 +-267.969,0.974461,0.831734,2,3,0,268.335,4.96176,2.21964,0.438859,0.247304 +-267.969,6.89728e-29,1.0963,1,1,0,270.705,4.96176,2.21964,0.438859,0.247304 +-272.266,0.795389,0.320267,3,15,0,275.898,4.85196,0.599511,0.261177,0.645477 +-271.269,1,0.32077,3,15,0,273.194,5.21065,2.51435,0.846259,0.101954 +-271.083,0.938627,0.439846,3,11,0,273.416,5.13792,1.25372,0.80931,0.18681 +# num_warmup = 350 +# Adaptation terminated +# Step size = 0.548013 +# Elements of inverse mass matrix: +# 0.0159681, 0.00128173, 0.0139713, -0.00490335 +# 0.00128173, 0.175196, 0.06337, -0.400566 +# 0.0139713, 0.06337, 0.3321, -0.0502834 +# -0.00490335, -0.400566, -0.0502834, 1.60018 +-271.086,0.98656,0.548013,3,7,0,271.708,5.08163,1.28631,0.807537,0.189048 +-271.474,0.489823,0.548013,2,3,0,275.679,4.96424,1.03752,0.74236,0.254156 +-268.982,0.996975,0.548013,3,7,0,272.303,5.22104,1.23295,0.647893,0.318526 +-267.26,0.975325,0.548013,3,7,0,270.063,4.94373,1.39562,0.57694,0.262899 +-271.505,0.681255,0.548013,2,3,0,272.041,4.81219,1.32011,0.677428,0.185478 +-269.226,0.911756,0.548013,2,3,0,273.29,4.9642,1.90313,0.690178,0.0998115 +-267.192,0.891323,0.548013,2,3,0,272.009,5.12291,1.74229,0.621608,0.183324 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+-267.779,0.97016,0.548013,3,7,0,269.129,5.15178,1.84026,0.642832,0.141358 +-267.795,0.953086,0.548013,2,3,0,268.546,5.12144,1.72542,0.577178,0.162559 +-266.783,0.978423,0.548013,3,7,0,268.466,5.00349,1.38009,0.484694,0.352419 +-268.756,0.905317,0.548013,2,3,0,269.049,5.00152,0.95193,0.67865,0.27373 +-269.936,0.967268,0.548013,3,7,0,271.858,5.02148,0.928917,0.496122,0.488861 +# +# Elapsed Time: 0.106411 seconds (Warm-up) +# 0.183567 seconds (Sampling) +# 0.289978 seconds (Total) +# diff --git a/examples/garch-garch11/mpi.1.output.csv b/examples/garch-garch11/mpi.1.output.csv new file mode 100644 index 0000000000..894dfc27a7 --- /dev/null +++ b/examples/garch-garch11/mpi.1.output.csv @@ -0,0 +1,1406 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = garch_garch11_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 1 +# data +# file = garch-garch11.data.R +# init = 2 (Default) +# random +# seed = 1569824 +# output +# file = mpi.1.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,mu,alpha0,alpha1,beta1 +-578.492,1,0.125,1,1,0,638.224,-1.18342,1.35172,0.219002,0.616366 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+-271.341,0.967155,0.291516,2,3,0,271.494,5.14364,0.622123,0.465637,0.528133 +-268.986,1,0.387936,3,7,0,272.824,5.25873,1.19705,0.641735,0.308453 +-269.531,0.686576,0.543846,3,7,0,273.652,5.0125,2.36534,0.726052,0.0631014 +-269.49,0.78392,0.454997,2,7,0,276.181,5.20127,2.33823,0.404465,0.249882 +-268.539,0.919816,0.446822,3,7,0,272.318,4.79637,1.55962,0.47218,0.330973 +-267.748,0.999231,0.54756,3,7,0,269.036,4.92705,1.81476,0.412375,0.322806 +-267.182,0.936035,0.762308,2,3,0,268.222,5.15345,1.39213,0.598266,0.246363 +-269.414,0.419466,0.956028,2,3,0,270.351,5.17935,1.60902,0.823175,0.113131 +-269.004,1,0.52037,3,7,0,269.495,5.16839,1.49196,0.801264,0.136848 +-267.176,0.662906,0.723099,2,3,0,270.689,5.01924,0.915881,0.512599,0.378528 +-267.72,0.972112,0.584171,2,3,0,267.832,4.97895,0.757746,0.479419,0.43832 +-267.623,0.660953,0.77444,2,3,0,269.739,5.13339,1.2341,0.600745,0.239141 +-267.817,0.995649,0.624388,3,7,0,268.419,5.18138,0.929949,0.532491,0.390333 +-268.663,0.68439,0.857534,2,3,0,269.277,5.14524,0.835048,0.524909,0.445406 +-269.946,0.989145,0.718217,2,7,0,271.571,5.03371,1.07856,0.65905,0.336388 +-269.946,0.00763709,0.973945,2,3,0,272.162,5.03371,1.07856,0.65905,0.336388 +-268.953,0.971042,0.281565,4,15,0,272.336,5.05369,1.51886,0.580226,0.154013 +-268.754,0.998375,0.371491,3,7,0,270.19,5.2342,1.59557,0.734464,0.204084 +-268.986,0.987244,0.510656,3,7,0,269.72,5.20703,1.59896,0.749763,0.211457 +-268.711,0.935023,0.688539,3,7,0,269.648,5.17118,1.63252,0.725807,0.231646 +-267.285,0.866772,0.854477,2,7,0,268.799,4.9626,1.17055,0.574452,0.347239 +-269.488,0.470123,0.952768,2,3,0,269.884,5.21286,1.88963,0.74721,0.202905 +-271.47,0.683043,0.575341,3,7,0,273.984,4.83706,1.36757,0.773836,0.198017 +-270.175,0.994144,0.483671,3,7,0,274.353,5.19106,1.38001,0.732272,0.259309 +-271.179,0.83761,0.656235,2,7,0,273.576,5.12711,1.15661,0.498999,0.48107 +# num_warmup = 350 +# Adaptation terminated +# Step size = 0.699374 +# Elements of inverse mass matrix: +# 0.0159681, 0.00128173, 0.0139713, -0.00490335 +# 0.00128173, 0.175196, 0.06337, -0.400566 +# 0.0139713, 0.06337, 0.3321, -0.0502834 +# -0.00490335, -0.400566, -0.0502834, 1.60018 +-268.149,0.916735,0.699374,3,7,0,272.418,4.94924,2.30074,0.552808,0.217564 +-268.533,0.910294,0.699374,2,3,0,268.978,4.89108,2.37193,0.499269,0.160614 +-267.818,1,0.699374,3,7,0,269.148,5.03684,0.853914,0.584232,0.375553 +-267.961,0.94334,0.699374,3,7,0,268.874,4.86008,1.19946,0.481178,0.344993 +-267.752,0.985535,0.699374,2,3,0,268.674,4.89507,1.45975,0.577853,0.312915 +-269.047,0.852421,0.699374,2,3,0,270.16,5.25157,2.00351,0.481311,0.195717 +-269.047,0.0061649,0.699374,2,3,0,276.91,5.25157,2.00351,0.481311,0.195717 +-267.479,0.991039,0.699374,2,3,0,269.693,5.03092,0.935542,0.594123,0.341964 +-269.161,0.66132,0.699374,3,7,0,271.121,5.23269,2.40902,0.683784,0.110584 +-267.608,0.909062,0.699374,2,3,0,271.533,5.02811,1.5082,0.55091,0.207969 +-269.651,0.324404,0.699374,3,7,0,270.099,5.20223,1.5261,0.788032,0.193334 +-267.604,0.987423,0.699374,2,3,0,270.17,5.01316,1.4818,0.703952,0.208756 +-267.804,0.931006,0.699374,2,3,0,268.55,4.96392,1.53098,0.627489,0.295403 +-269.188,0.918025,0.699374,2,3,0,269.896,5.26774,1.85233,0.499986,0.195717 +-268.154,0.624738,0.699374,2,3,0,270.728,5.06096,1.26071,0.66233,0.308267 +-266.898,0.986262,0.699374,2,3,0,268.194,5.00161,1.43588,0.603903,0.267752 +-268.18,0.714823,0.699374,2,3,0,268.681,4.88751,1.05335,0.362696,0.481163 +-268.089,0.460919,0.699374,3,7,0,271.296,5.24255,1.2755,0.587333,0.295959 +-267.437,0.761479,0.699374,2,3,0,271.078,5.02621,1.04405,0.436996,0.45942 +-267.674,0.966502,0.699374,2,3,0,268.602,5.15022,0.933366,0.585277,0.342504 +-267.702,0.898275,0.699374,3,7,0,268.661,4.89025,0.993413,0.443361,0.438049 +-268.008,0.901137,0.699374,3,7,0,268.803,5.20131,1.44269,0.519461,0.349078 +-268.448,0.912755,0.699374,3,7,0,269.717,4.9342,1.7378,0.614321,0.154303 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+-267.244,0.882685,0.699374,2,3,0,268.544,4.96344,1.10435,0.417745,0.404314 +-267.244,1.26145e-15,0.699374,2,3,0,279.303,4.96344,1.10435,0.417745,0.404314 +# +# Elapsed Time: 0.105212 seconds (Warm-up) +# 0.148451 seconds (Sampling) +# 0.253663 seconds (Total) +# diff --git a/examples/garch-garch11/mpi.2.output.csv b/examples/garch-garch11/mpi.2.output.csv new file mode 100644 index 0000000000..f76a6e2245 --- /dev/null +++ b/examples/garch-garch11/mpi.2.output.csv @@ -0,0 +1,1406 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = garch_garch11_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 2 +# data +# file = garch-garch11.data.R +# init = 2 (Default) +# random +# seed = 1569824 +# output +# file = mpi.2.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,mu,alpha0,alpha1,beta1 +-426.132,1,0.25,2,3,0,505.992,1.69384,17.8206,0.486779,0.301825 +-426.132,0,14.3855,0,1,1,426.274,1.69384,17.8206,0.486779,0.301825 +-426.132,0,2.43117,0,1,1,426.669,1.69384,17.8206,0.486779,0.301825 +-372.485,1,0.239791,1,3,0,429.016,2.38191,7.46724,0.389119,0.241312 +-305.819,1,0.324332,1,1,0,369.536,4.87164,9.3944,0.416185,0.184202 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+-268.409,0.937385,0.722756,2,7,0,270.138,5.21143,1.19698,0.657398,0.295649 +-267.081,0.956928,0.905005,2,3,0,268.582,5.10331,1.20663,0.471569,0.341705 +-267.276,0.565946,1.16653,2,3,0,267.786,5.04395,1.42647,0.631929,0.29024 +-267.089,0.499008,0.819272,2,3,0,268.243,5.02745,1.02001,0.476098,0.427308 +-268.176,0.74606,0.51995,2,3,0,269.166,4.99959,1.0623,0.351835,0.432066 +-268.061,0.849111,0.484031,3,7,0,269.402,4.98792,1.96454,0.577469,0.276511 +-270.289,0.95988,0.528045,2,7,0,272.682,5.27923,1.65842,0.812053,0.156515 +# num_warmup = 350 +# Adaptation terminated +# Step size = 0.682151 +# Elements of inverse mass matrix: +# 0.0159681, 0.00128173, 0.0139713, -0.00490335 +# 0.00128173, 0.175196, 0.06337, -0.400566 +# 0.0139713, 0.06337, 0.3321, -0.0502834 +# -0.00490335, -0.400566, -0.0502834, 1.60018 +-267.856,0.578815,0.682151,3,7,0,271.717,5.06793,2.09642,0.673153,0.120671 +-268.971,0.935779,0.682151,3,7,0,269.679,5.23431,1.27654,0.558618,0.374154 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+-268.2,1,0.682151,2,3,0,270.073,5.02745,1.67017,0.68838,0.255001 +-268.808,0.999663,0.682151,2,3,0,269.064,5.12183,1.51634,0.788153,0.182856 +-269.675,0.499371,0.682151,3,7,0,273.694,5.02874,1.20191,0.784966,0.192646 +-269.051,1,0.682151,1,1,0,269.785,5.00861,1.26014,0.759268,0.214972 +-267.654,0.671296,0.682151,2,3,0,270.188,5.06445,1.33036,0.597273,0.342422 +-269.212,0.762619,0.682151,2,3,0,269.71,5.09905,0.96727,0.643946,0.234032 +-267.091,0.983129,0.682151,2,3,0,269.41,5.01738,1.04938,0.577499,0.342104 +-267.989,0.925123,0.682151,2,3,0,268.595,5.13128,2.11923,0.704423,0.135815 +-268.012,0.955361,0.682151,3,7,0,268.743,5.13792,1.5816,0.717462,0.146137 +-270.2,0.852984,0.682151,3,7,0,270.96,5.10579,2.00183,0.869666,0.0965256 +# +# Elapsed Time: 0.106088 seconds (Warm-up) +# 0.154162 seconds (Sampling) +# 0.26025 seconds (Total) +# diff --git a/examples/garch-garch11/mpi.3.output.csv b/examples/garch-garch11/mpi.3.output.csv new file mode 100644 index 0000000000..186aab57b3 --- /dev/null +++ b/examples/garch-garch11/mpi.3.output.csv @@ -0,0 +1,1406 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = garch_garch11_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 3 +# data +# file = garch-garch11.data.R +# init = 2 (Default) +# random +# seed = 1569824 +# output +# file = mpi.3.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,mu,alpha0,alpha1,beta1 +-330.786,1,0.25,2,3,0,474.819,5.86936,12.8756,0.802832,0.0789824 +-330.786,0,14.3855,0,1,1,331.721,5.86936,12.8756,0.802832,0.0789824 +-330.786,0,2.43117,0,1,1,331.339,5.86936,12.8756,0.802832,0.0789824 +-281.992,1,0.239791,1,1,0,317.012,5.60496,3.60589,0.837644,0.0602237 +-281.992,6.51213e-80,0.324332,1,1,0,284.916,5.60496,3.60589,0.837644,0.0602237 +-280.377,0.998923,0.0257257,3,7,0,282.862,5.5614,3.50052,0.833948,0.0639916 +-271.382,1,0.0402734,4,15,0,281.25,5.27941,2.47737,0.836196,0.0670997 +-271.523,0.997872,0.0684943,3,7,0,271.789,5.29212,2.48726,0.834177,0.0695638 +-270.419,0.99356,0.12157,4,15,0,271.538,4.96826,2.39276,0.818316,0.074334 +-268.978,0.488623,0.219293,3,15,0,271.448,5.08367,2.17577,0.746151,0.0770908 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+-270.182,0.869169,0.421996,3,7,0,273.008,4.85514,1.03363,0.552258,0.430243 +-270.786,0.996121,0.480506,3,7,0,272.233,5.19273,0.892014,0.584687,0.410752 +-269.769,0.781824,0.682951,2,3,0,271.524,5.13175,0.948106,0.632418,0.361472 +-268.363,0.941711,0.665618,3,7,0,270.641,5.03897,1.46181,0.729946,0.153681 +-267.371,0.989931,0.85715,2,3,0,268.586,5.11461,1.32904,0.671693,0.25491 +-267.371,0.0823521,1.19782,1,1,0,269.322,5.11461,1.32904,0.671693,0.25491 +-268.237,0.981763,0.347812,3,7,0,269.019,5.17037,2.10181,0.602675,0.119491 +-269.441,0.797383,0.479649,3,7,0,271.576,5.27238,1.7018,0.765336,0.173599 +-267.64,0.984414,0.480921,2,7,0,269.814,5.13526,1.53377,0.709774,0.175213 +-269.606,0.824378,0.663848,2,3,0,270.064,5.03208,1.64247,0.771213,0.0988601 +-266.997,0.999183,0.696067,3,7,0,269.542,5.01083,1.33767,0.570781,0.261634 +-267.402,0.938078,0.981593,1,3,0,267.584,4.90976,1.07228,0.50552,0.38107 +-267.402,0.176,1.24526,2,3,0,269.152,4.90976,1.07228,0.50552,0.38107 +-267.255,0.986452,0.436589,3,7,0,268.377,5.06447,0.868823,0.507031,0.391265 +-267.276,0.991782,0.60142,2,7,0,267.464,5.09468,0.887641,0.530458,0.384617 +-267.092,0.917782,0.834021,1,3,0,268.396,4.99348,1.3933,0.529352,0.353271 +-267.502,0.858954,1.01997,2,3,0,267.901,5.13495,1.34742,0.474408,0.386874 +-267.513,1,1.1296,2,3,0,267.804,5.07746,2.19572,0.556738,0.159551 +-267.513,0.00246254,1.57913,1,1,0,269.273,5.07746,2.19572,0.556738,0.159551 +-268.581,0.937833,0.424404,3,7,0,270.047,4.92881,1.71444,0.650825,0.150668 +-268.104,0.905421,0.536159,2,3,0,270.191,5.00313,1.18229,0.604402,0.235592 +-268.271,0.98654,0.641264,3,7,0,270.561,4.91871,0.77347,0.450227,0.433649 +-268.271,0.0111776,0.874639,2,3,0,271.153,4.91871,0.77347,0.450227,0.433649 +-267.172,0.999944,0.243087,4,15,0,268.816,5.1213,0.980677,0.520579,0.369397 +-266.84,0.987415,0.339223,2,7,0,268.001,5.06502,1.29463,0.458017,0.359364 +-267.677,0.806819,0.462858,2,3,0,268.713,5.16185,1.00301,0.507637,0.410808 +-267.647,0.930019,0.470998,3,7,0,270.714,4.92007,1.0016,0.501177,0.421278 +-267.683,0.955506,0.584193,3,7,0,269.513,5.19597,1.64219,0.599252,0.195859 +-267.683,0.14448,0.753747,1,1,0,270.445,5.19597,1.64219,0.599252,0.195859 +-268.023,0.99605,0.265766,4,15,0,268.571,4.92223,0.911789,0.506257,0.438575 +-269.696,0.978294,0.366078,3,7,0,270.262,5.27708,2.41999,0.602854,0.100669 +-267.871,0.999729,0.489242,3,7,0,270.108,5.01239,1.19765,0.433206,0.45806 +-271.39,0.817229,0.675166,3,7,0,271.96,4.89891,3.22571,0.401364,0.0532684 +-267.665,0.925884,0.69724,2,3,0,272.028,5.01264,1.53155,0.5655,0.338646 +-268.031,0.977246,0.854038,2,7,0,268.304,4.91527,1.24488,0.529593,0.278116 +-270.289,0.260514,1.1324,2,3,0,271.67,5.19429,0.975383,0.759677,0.213037 +-269.009,1,0.488878,3,7,0,271.367,5.00856,2.67492,0.58345,0.0759342 +-267.107,0.792247,0.671591,2,3,0,270.107,4.97413,1.62445,0.456057,0.294189 +-268.082,0.837425,0.66678,2,3,0,269.497,5.09151,1.03303,0.682627,0.267707 +-268.661,0.816433,0.710015,2,3,0,270.577,4.86624,1.49972,0.463,0.406954 +-270.943,0.381954,0.73165,3,7,0,271.936,4.92092,2.30142,0.570331,0.305634 +-268.888,0.994654,0.386084,3,7,0,272.191,4.8858,1.9706,0.682364,0.206985 +-269.755,0.937832,0.5239,2,7,0,271.397,5.18225,1.00965,0.66495,0.326185 +# num_warmup = 350 +# Adaptation terminated +# Step size = 0.650508 +# Elements of inverse mass matrix: +# 0.0159681, 0.00128173, 0.0139713, -0.00490335 +# 0.00128173, 0.175196, 0.06337, -0.400566 +# 0.0139713, 0.06337, 0.3321, -0.0502834 +# -0.00490335, -0.400566, -0.0502834, 1.60018 +-270.691,0.808565,0.650508,2,7,0,273.081,5.03978,2.75516,0.773555,0.126091 +-268.493,1,0.650508,2,7,0,272.601,5.19387,1.4378,0.484731,0.250696 +-268.263,1,0.650508,3,7,0,269.913,4.98009,1.56161,0.718351,0.162894 +-269.12,0.744665,0.650508,2,7,0,269.962,5.17173,1.74529,0.810244,0.106948 +-269.855,0.904775,0.650508,3,7,0,271.03,5.11663,1.13836,0.493816,0.470119 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+-267.295,0.938598,0.650508,2,7,0,268.428,5.13271,1.42473,0.485735,0.358238 +-269.396,0.697409,0.650508,2,3,0,270.139,4.99152,0.70002,0.59488,0.389991 +-269.497,0.524777,0.650508,2,3,0,273.613,5.12223,0.967818,0.426238,0.517163 +-271.167,0.859244,0.650508,2,7,0,272.694,5.30446,1.0098,0.735546,0.210053 +-268.71,1,0.650508,2,3,0,272.292,5.27314,1.31636,0.597035,0.307709 +-268.066,0.979615,0.650508,3,7,0,269.707,5.10958,1.10942,0.69396,0.266131 +-270.275,0.880389,0.650508,2,7,0,270.408,5.06,1.77003,0.621835,0.337162 +-267.193,1,0.650508,3,7,0,269.819,5.12033,1.21744,0.459373,0.351039 +-266.81,0.986586,0.650508,2,7,0,267.847,5.03678,1.55356,0.482852,0.297133 +-267.285,0.938383,0.650508,2,3,0,267.543,4.91589,1.31852,0.551268,0.308242 +-267.022,0.948324,0.650508,3,7,0,268.21,5.142,1.54018,0.595358,0.250166 +-266.794,0.930574,0.650508,3,7,0,267.794,4.97975,1.35116,0.485812,0.334048 +-266.908,0.937702,0.650508,2,7,0,267.288,5.06735,1.19235,0.515793,0.315772 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+-271.823,0.835442,0.650508,2,3,0,272.096,5.28197,1.72107,0.882475,0.100724 +-267.93,1,0.650508,2,3,0,272.685,5.11256,1.61433,0.569073,0.326671 +-268.066,0.982717,0.650508,2,7,0,268.274,5.00993,1.4585,0.616988,0.181032 +-267.827,0.992783,0.650508,2,7,0,268.707,5.11291,2.05088,0.695774,0.165688 +-267.992,0.789573,0.650508,3,7,0,270.311,5.05716,0.697035,0.464608,0.475801 +-267.481,0.861835,0.650508,3,7,0,268.821,5.00627,2.11585,0.480489,0.210575 +-268.073,0.834393,0.650508,2,3,0,268.901,4.99785,2.21602,0.49428,0.263253 +-267.404,1,0.650508,3,7,0,268.344,4.96077,0.882217,0.491413,0.407257 +-268.413,0.895647,0.650508,2,3,0,269.216,5.22127,0.912599,0.492168,0.423113 +-268.669,0.973208,0.650508,3,7,0,270.104,5.2626,1.86095,0.543713,0.251804 +-268.565,0.860877,0.650508,3,7,0,271.361,5.03914,1.7027,0.397706,0.407348 +-268.365,0.990965,0.650508,3,7,0,269.217,5.19899,1.42195,0.681175,0.266259 +-268.214,0.818093,0.650508,3,7,0,269.589,4.93325,1.04917,0.572434,0.388154 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+-267.416,0.970642,0.650508,2,7,0,268.218,5.03796,0.933868,0.429667,0.412484 +-267.852,0.546465,0.650508,3,7,0,271.398,4.96052,1.97838,0.661765,0.158647 +-269.735,0.443586,0.650508,1,3,0,273.884,4.75843,1.5424,0.395059,0.326302 +-268.939,1,0.650508,1,1,0,269.793,4.79374,1.62692,0.421605,0.307512 +-271.155,0.973372,0.650508,2,3,0,271.55,4.73817,1.09684,0.293383,0.546032 +-269.881,0.530387,0.650508,3,7,0,275.162,5.22881,1.78724,0.829741,0.0950573 +-271.366,0.521888,0.650508,3,7,0,274.987,5.00555,1.19863,0.829675,0.14685 +-269.408,0.853221,0.650508,2,7,0,273.665,4.95998,1.95264,0.75856,0.0981532 +-268.368,0.965995,0.650508,2,3,0,270.346,5.00502,1.31249,0.737612,0.204599 +-269.972,0.811725,0.650508,3,7,0,271.776,5.10018,0.535636,0.522976,0.46376 +-267.567,1,0.650508,2,3,0,270.336,5.08834,1.357,0.575238,0.22181 +-267.442,0.876279,0.650508,3,7,0,268.498,5.01196,1.53872,0.685443,0.226347 +-267.293,0.864941,0.650508,3,7,0,268.505,5.10652,1.07601,0.561812,0.302588 +-268.715,0.710841,0.650508,2,3,0,269.164,5.11639,0.939751,0.471534,0.336876 +-267.709,1,0.650508,3,7,0,268.609,5.15345,0.953391,0.444032,0.412275 +-270.474,0.919421,0.650508,2,7,0,270.964,4.95127,0.51508,0.529506,0.419651 +-267.696,1,0.650508,2,3,0,270.985,4.89118,1.13747,0.400378,0.431443 +-267.983,0.60638,0.650508,3,7,0,270.693,5.1318,0.903125,0.617385,0.338347 +-267.216,0.964848,0.650508,2,3,0,268.475,5.06616,1.2839,0.649577,0.278401 +-268.504,0.856615,0.650508,2,3,0,269.395,5.23065,1.89069,0.707706,0.132923 +# +# Elapsed Time: 0.107356 seconds (Warm-up) +# 0.162855 seconds (Sampling) +# 0.270211 seconds (Total) +# diff --git a/examples/radon/radon.data.R b/examples/radon/radon.data.R new file mode 100644 index 0000000000..4c0dbb1dc3 --- /dev/null +++ b/examples/radon/radon.data.R @@ -0,0 +1,3830 @@ +N <- 12573 +J <- 386 +x <- +c(9, 1, 1, 1, 1, 9, 1, 1, 1, 9, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 9, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 9, 1, 1, 1, 9, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, +1, 9, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 9, 1, 1, 0, 1, 9, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, +1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, +1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9, 1, 9, 1, 1, 1, 1, 1, 1, 1, 9, 1, 9, 9, 1, 1, 9, 1, 1, 1, 1, 1, +1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, +1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 9, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, +1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 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1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, +1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, +1, 1, 1, 1, 9, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, +1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 2, 1, 1, 1, +1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, +1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 9, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, +1, 9, 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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, +0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, +0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0) diff --git a/examples/radon/radon.stan b/examples/radon/radon.stan new file mode 100644 index 0000000000..242f455375 --- /dev/null +++ b/examples/radon/radon.stan @@ -0,0 +1,23 @@ +data { + int N; + int J; + int county[N]; + vector[N] y; +} + +parameters { + vector[J] a; + real mu_a; + real sigma_a; + real sigma_y; +} + +model { + vector[N] y_hat; + for (i in 1:N) + y_hat[i] = a[county[i]]; + + mu_a ~ normal(0, 1); + a ~ normal (mu_a, sigma_a); + y ~ normal(y_hat, sigma_y); +} diff --git a/examples/radon/readme.md b/examples/radon/readme.md new file mode 100644 index 0000000000..28b05da36e --- /dev/null +++ b/examples/radon/readme.md @@ -0,0 +1,58 @@ +- [Get the repo & depdencies](#org5557ab1) + - [Edit make/local](#org32e15b8) + - [Compile](#org5d3f69c) + - [Run](#orgafcbab4) + + + + +# Get the repo & depdencies + +```bash +git clone --recurse-submodules --single-branch --branch mpi_warmup_framework git@github.com:stan-dev/cmdstan.git +``` + + + + +# Edit make/local + +```bash +MPI_ADAPTED_WARMUP = 1 +CXXFLAGS += -isystem /path/to/mpi/headers +TBB_CXX_TYPE=clang # your cpp compiler +``` + + + + +# Compile + +```bash +make clean-all; +make -j4 examples/radon/radon +``` + + + + +# Run + +```bash +mpiexec -n 4 -l ./radon sample adapt num_cross_chains=4 cross_chain_window=100 data file=radon.data.R # MPICH +mpiexec -n 4 --tag-output ./radon sample adapt num_cross_chains=4 cross_chain_window=100 data file=radon.data.R # OpenMPI +``` + +runs 4 chains with cross-chain warmup, using 4 processes. Here + +```bash +num_cross_chains= +``` + +specifies the number of parallel chains used in cross-chain warmup(default 4), and + +```bash +cross_chain_window= +``` + +specifies that every `cross_chain_window` iterations(default 100) the convergence check is performed using data collected from the chains. See for details. diff --git a/examples/radon/readme.org b/examples/radon/readme.org new file mode 100644 index 0000000000..6cbebdb262 --- /dev/null +++ b/examples/radon/readme.org @@ -0,0 +1,38 @@ +** Get the repo & depdencies +#+BEGIN_SRC bash +git clone --recurse-submodules --single-branch --branch mpi_warmup_framework git@github.com:stan-dev/cmdstan.git +#+END_SRC + +** Edit make/local +#+BEGIN_SRC bash + MPI_ADAPTED_WARMUP = 1 + CXXFLAGS += -isystem /path/to/mpi/headers + TBB_CXX_TYPE=clang # your cpp compiler +#+END_SRC + +** Compile +#+BEGIN_SRC bash +make clean-all; +make -j4 examples/radon/radon +#+END_SRC + +** Run +#+BEGIN_SRC bash + mpiexec -n 4 -l ./radon sample adapt num_cross_chains=4 cross_chain_window=100 data file=radon.data.R # MPICH + mpiexec -n 4 --tag-output ./radon sample adapt num_cross_chains=4 cross_chain_window=100 data file=radon.data.R # OpenMPI +#+END_SRC +runs 4 chains with cross-chain warmup, using 4 +processes. Here +#+BEGIN_SRC bash +num_cross_chains= +#+END_SRC +specifies the number of parallel chains used in cross-chain +warmup(default 4), and +#+BEGIN_SRC bash +cross_chain_window= +#+END_SRC +specifies that every =cross_chain_window= +iterations(default 100) the +convergence check is performed using data collected from the +chains. See https://discourse.mc-stan.org/t/new-adaptive-warmup-proposal-looking-for-feedback/12039 +for details. diff --git a/examples/radon/stdout.dat b/examples/radon/stdout.dat new file mode 100644 index 0000000000..9a8de6aff3 --- /dev/null +++ b/examples/radon/stdout.dat @@ -0,0 +1,166 @@ +mpiexec -n 5 -l ./radon sample data file=radon.data.R output file=output.csv +[0] method = sample (Default) +[0] sample +[0] num_samples = 1000 (Default) +[0] num_warmup = 1000 (Default) +[0] save_warmup = 0 (Default) +[0] thin = 1 (Default) +[0] adapt +[0] engaged = 1 (Default) +[0] gamma = 0.050000000000000003 (Default) +[0] delta = 0.80000000000000004 (Default) +[0] kappa = 0.75 (Default) +[0] t0 = 10 (Default) +[0] init_buffer = 75 (Default) +[0] term_buffer = 50 (Default) +[0] window = 25 (Default) +[0] algorithm = hmc (Default) +[0] hmc +[0] engine = nuts (Default) +[0] nuts +[0] max_depth = 10 (Default) +[0] metric = diag_e (Default)[0] +[0] metric_file = (Default) +[0] stepsize = 1 (Default) +[0] stepsize_jitter = 0 (Default) +[0] id = 0 (Default) +[0] data +[0] file = radon.data.R +[0] init = 2 (Default) +[0] random +[0] seed = -1 (Default) +[0] output +[0] file = output.csv (Default) +[0] diagnostic_file = (Default) +[0] refresh = 100 (Default) +[0] +[0] +[0] Gradient evaluation took 0.000725 seconds +[0] 1000 transitions using 10 leapfrog steps per transition would take 7.25 seconds. +[0] Adjust your expectations accordingly! +[0] +[0] +[3] +[3] Gradient evaluation took 0.000732 seconds +[3] 1000 transitions using 10 leapfrog steps per transition would take 7.32 seconds. +[3] Adjust your expectations accordingly! +[3] +[3] +[4] +[4] Gradient evaluation took 0.000717 seconds +[4] 1000 transitions using 10 leapfrog steps per transition would take 7.17 seconds. +[4] Adjust your expectations accordingly! +[4] +[4] +[1] +[1] Gradient evaluation took 0.000936 seconds +[1] 1000 transitions using 10 leapfrog steps per transition would take 9.36 seconds. +[1] Adjust your expectations accordingly! +[1] +[1] +[2] +[2] Gradient evaluation took 0.000954 seconds +[2] 1000 transitions using 10 leapfrog steps per transition would take 9.54 seconds. +[2] Adjust your expectations accordingly! +[2] +[2] +[3] Iteration: 1 / 2000 [ 0%] (Warmup) +[0] Iteration: 1 / 2000 [ 0%] (Warmup) +[4] Iteration: 1 / 2000 [ 0%] (Warmup) +[1] Iteration: 1 / 2000 [ 0%] (Warmup) +[2] Iteration: 1 / 2000 [ 0%] (Warmup) +[4] Iteration: 100 / 2000 [ 5%] (Warmup) +[3] Iteration: 100 / 2000 [ 5%] (Warmup) +[2] Iteration: 100 / 2000 [ 5%] (Warmup) +[0] Iteration: 100 / 2000 [ 5%] (Warmup) +[1] Iteration: 100 / 2000 [ 5%] (Warmup) +[2] Iteration: 200 / 2000 [ 10%] (Warmup) +[4] Iteration: 200 / 2000 [ 10%] (Warmup) +[0] Iteration: 200 / 2000 [ 10%] (Warmup) +[3] Iteration: 200 / 2000 [ 10%] (Warmup) +[1] Iteration: 200 / 2000 [ 10%] (Warmup) +[0] Iteration: 300 / 2000 [ 15%] (Warmup) +[4] Iteration: 300 / 2000 [ 15%] (Warmup) +[2] Iteration: 300 / 2000 [ 15%] (Warmup) +[3] Iteration: 300 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13.7925 seconds (Total) +[3] +[0] Iteration: 2000 / 2000 [100%] (Sampling) +[0] +[0] Elapsed Time: 8.04967 seconds (Warm-up) +[0] 5.93972 seconds (Sampling) +[0] 13.9894 seconds (Total) +[0] diff --git a/examples/run_cc.R b/examples/run_cc.R new file mode 100644 index 0000000000..cdb015fac0 --- /dev/null +++ b/examples/run_cc.R @@ -0,0 +1,101 @@ +## Aki's summary script +perf.cc <- function(stanfit) { + (n_warmup = stanfit@sim$warmup) + n_iter = stanfit@sim$iter-n_warmup + sampler_params <- rstan:::get_sampler_params(stanfit, inc_warmup = TRUE) + leapfrogs = sapply(sampler_params, function(x) x[, "n_leapfrog__"]) + (sum_warmup_leapfrogs = sum(leapfrogs[1:n_warmup,])) + (sum_leapfrogs = sum(leapfrogs[n_warmup+(1:n_iter),])) + (mean_warmup_leapfrogs = sum_warmup_leapfrogs/n_warmup) + (mean_leapfrogs = sum_leapfrogs/n_iter) + mon = rstan::monitor(as.array(stanfit), warmup=0, print=FALSE) + (maxrhat = max(mon[,'Rhat'])) + bulk_ess_per_iter = mon[,'Bulk_ESS']/n_iter + tail_ess_per_iter = mon[,'Tail_ESS']/n_iter + bulk_ess_per_leapfrog = mon[,'Bulk_ESS']/sum_leapfrogs + tail_ess_per_leapfrog = mon[,'Tail_ESS']/sum_leapfrogs + min(bulk_ess_per_iter) + min(tail_ess_per_iter) + min(bulk_ess_per_leapfrog) + min(tail_ess_per_leapfrog) + (stepsizes = sapply(sampler_params, function(x) x[, "stepsize__"])[n_iter,]) + + res <- data.frame(run = c(sum_warmup_leapfrogs, sum_leapfrogs, + mean_warmup_leapfrogs, mean_leapfrogs, + min(bulk_ess_per_iter), min(tail_ess_per_iter), min(bulk_ess_per_leapfrog), min(tail_ess_per_leapfrog))) + row.names(res) <- c("warmup.leapfrogs", "leapfrogs", + "mean.warmup.leapfrogs", "mean.leapfrogs", + "min(bulk_ess/iter)", "min(tail_ess/iter)", "min(bulk_ess/leapfrog)", "min(tail_ess/leapfrog)") + return(res) +} + +## run both cross-chain & regular warmup version and output summary +run.cc.metric <- function(modelpath, model, metric, seed, adapt.arg="") { + model.file = paste(model,"stan", sep="") + data.file = paste(model,".data.R", sep="") + system(paste("make -j4 ", file.path(modelpath, model, model), sep="")) + cmdwd <- getwd(); + + setwd(file.path(modelpath, model)) + + system(paste("mpiexec -n 4 -l -bind-to core ./", model, " sample save_warmup=1 algorithm=hmc metric=", metric, " adapt ", adapt.arg, " data file=", data.file, " random seed=", seed, " ",sep="")) + fit.mpi <- rstan::read_stan_csv(dir(pattern="mpi.[0-3].output.csv", full.name=TRUE)) + system(paste("for i in {0..3}; do ./", model, " sample save_warmup=1 algorithm=hmc metric=", metric, " adapt ", adapt.arg, " data file=", data.file, " random seed=", seed, " output file=$i.output.csv id=$i;done", " ",sep="")) + fit.seq <- rstan::read_stan_csv(dir(pattern="^[0-3].output.csv", full.name=TRUE)) + summary <- data.frame(perf.cc(fit.mpi), perf.cc(fit.seq)) + colnames(summary) <- c(paste0("MPI.",metric), paste0("regular.",metric)) + + setwd(cmdwd) + return(list(mpi=fit.mpi, seq=fit.seq, summary=summary)) +} + +## run cross-chain & regular warmup for both diag & dense metric +run.cc <- function(modelpath, model, adapt.arg="") { + seed = sample(999999:9999999, 1) + + fits.diag <- run.cc.metric(modelpath, model, "diag_e", seed, adapt.arg) + fits.dense <- run.cc.metric(modelpath, model, "dense_e", seed, adapt.arg) + + library("gridExtra") + library("bayesplot") + library("dplyr") + ## pdf(paste0(model, "_cross_chain_summary.pdf"), paper="a4") + ## grid.table(format(cbind(fits.diag[["summary"]], fits.dense[["summary"]]), digits=3)) + ## lp <- log_posterior(fits.diag[["mpi"]]) + ## np <- nuts_params(fits.diag[["mpi"]]) + ## p <- grid.arrange(mcmc_nuts_divergence(np, lp),top="mcmc_nuts_divergence: cross-chain + diag_e") + ## print(p) + ## lp <- log_posterior(fits.diag[["seq"]]) + ## np <- nuts_params(fits.diag[["seq"]]) + ## p <- grid.arrange(mcmc_nuts_divergence(np, lp),top="mcmc_nuts_divergence: regular + diag_e") + ## print(p) + ## lp <- log_posterior(fits.dense[["mpi"]]) + ## np <- nuts_params(fits.dense[["mpi"]]) + ## p <- grid.arrange(mcmc_nuts_divergence(np, lp),top="mcmc_nuts_divergence: cross-chain + dense_e") + ## print(p) + ## lp <- log_posterior(fits.dense[["seq"]]) + ## np <- nuts_params(fits.dense[["seq"]]) + ## p <- grid.arrange(mcmc_nuts_divergence(np, lp),top="mcmc_nuts_divergence: regular + dense_e") + ## print(p) + ## dev.off() + + grid.table(format(cbind(fits.diag[["summary"]], fits.dense[["summary"]]), digits=3)) + + d <- cbind(fits.diag[["summary"]], fits.dense[["summary"]]) + d%>% + tibble::rownames_to_column()%>% + tidyr::gather('col','val',-rowname)%>% + tidyr::separate(col,c('type','metric'),sep='\\.')%>% + dplyr::filter(grepl('',rowname))%>% + ggplot2::ggplot(ggplot2::aes(x=metric,y=val,fill=type)) + + ggplot2::geom_bar(stat = 'identity',position = ggplot2::position_dodge()) + + ggplot2::facet_wrap(~rowname,scales='free') + + ggplot2::ggsave(file=paste0(paste0(model, "_cross_chain_summary.png"))) + + return(list(summary=cbind(fits.diag[["summary"]], fits.dense[["summary"]]), + mpi.diag=fits.diag[["mpi"]], + seq.diag=fits.diag[["seq"]], + mpi.dense=fits.dense[["mpi"]], + seq.dense=fits.dense[["seq"]])) +} diff --git a/examples/sblrc-blr/0.output.csv b/examples/sblrc-blr/0.output.csv new file mode 100644 index 0000000000..f8f1bf0665 --- /dev/null +++ b/examples/sblrc-blr/0.output.csv @@ -0,0 +1,2058 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = sblrc_blr_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 0 (Default) +# data +# file = sblrc-blr.data.R +# init = 2 (Default) +# random +# seed = 1540963 +# output +# file = 0.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +-11460.1,1,0.00195312,2,3,0,286050,-0.049438,0.256602,0.322383,-0.0698726,-0.835327,17.6816 +-11460.1,0,14.3855,0,1,1,11461.9,-0.049438,0.256602,0.322383,-0.0698726,-0.835327,17.6816 +-11460.1,0,2.43117,0,1,1,11462.5,-0.049438,0.256602,0.322383,-0.0698726,-0.835327,17.6816 +-11460.1,0,0.239791,0,1,1,11465,-0.049438,0.256602,0.322383,-0.0698726,-0.835327,17.6816 +-11460.1,0,0.0186273,0,1,1,11460.6,-0.049438,0.256602,0.322383,-0.0698726,-0.835327,17.6816 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+-169.853,0.674587,0.149578,2,3,0,172.828,1.00185,1.00013,1.00088,1.00128,0.999367,1.02709 +-165.548,1,0.110583,2,3,0,170.498,1.00138,0.999844,1.00001,1.00084,1.0009,1.03623 +-163.852,0.977262,0.190688,3,15,0,166.399,0.999866,1.00013,0.998817,0.999793,0.999484,1.07464 +-163.935,0.207148,0.307549,2,5,0,164.762,0.999971,0.99893,0.999584,0.998991,0.998961,1.08291 +-163.058,0.991907,0.0691495,4,31,0,165.164,1.0004,0.999496,0.99918,0.999075,0.998918,1.06679 +-164.08,0.9136,0.115765,2,7,0,165.31,0.999753,0.998002,0.998551,0.99905,0.999199,1.07407 +-164.365,0.939527,0.157977,2,3,0,165.615,1.00033,0.999085,0.998197,0.998367,0.99826,1.07712 +-164.012,0.706624,0.2289,3,15,0,165.07,0.999221,0.999134,0.99798,0.99952,0.998944,0.971859 +-166.129,0.388815,0.185363,2,3,0,169.618,0.999712,0.997748,0.998715,0.997856,0.998135,0.951327 +-163.347,0.9898,0.0689584,4,31,0,170.525,0.999439,0.998295,0.998214,0.998145,0.998451,1.12997 +-164.073,0.937239,0.112688,4,15,0,165.2,0.999629,0.999144,0.998711,0.999468,0.998563,1.16037 +-164.451,0.946742,0.161,4,15,0,165.652,0.999551,0.998067,0.99785,0.998063,0.998674,1.16707 +-164.451,0.0980377,0.234158,2,7,0,171.783,0.999551,0.998067,0.99785,0.998063,0.998674,1.16707 +-163.663,0.995903,0.0446016,4,15,0,165.46,0.999287,0.998624,0.998437,0.998891,0.998323,1.15399 +-164.997,0.998466,0.0731422,5,31,0,165.552,1.0009,0.999871,0.999736,1.00045,0.999711,1.18538 +# num_warmup = 1000 +# Adaptation terminated +# Step size = 0.114275 +# Elements of inverse mass matrix: +# 1.08623e-05, 7.19842e-07, 8.0785e-07, 7.59186e-07, 8.05676e-07, 1.05898e-05 +# 7.19842e-07, 1.08741e-05, 8.02648e-07, 7.76347e-07, 7.18375e-07, 9.49904e-06 +# 8.0785e-07, 8.02648e-07, 1.10351e-05, 8.30694e-07, 8.30937e-07, 1.35116e-05 +# 7.59186e-07, 7.76347e-07, 8.30694e-07, 1.08444e-05, 7.70188e-07, 1.16131e-05 +# 8.05676e-07, 7.18375e-07, 8.30937e-07, 7.70188e-07, 1.0852e-05, 1.19759e-05 +# 1.05898e-05, 9.49904e-06, 1.35116e-05, 1.16131e-05, 1.19759e-05, 0.00609624 +-164.06,0.989718,0.114275,4,15,0,166.28,0.998438,0.998031,0.997563,0.998011,0.997645,1.15553 +-164.043,0.892374,0.114275,2,7,0,165.877,0.999174,0.997588,0.997698,0.99864,0.998172,1.13672 +-163.749,0.957793,0.114275,4,23,0,165.645,0.998942,0.998263,0.997132,0.998714,0.998613,1.06806 +-164.935,0.94344,0.114275,3,7,0,166.266,0.999517,0.998292,0.999211,0.999045,0.999404,1.06172 +-164.15,0.951709,0.114275,3,7,0,167.377,0.998913,0.99891,0.998674,0.998396,0.998794,1.06784 +-163.236,0.943227,0.114275,3,15,0,166.659,0.999412,0.998246,0.997382,0.998295,0.997439,1.04687 +-164.628,0.933165,0.114275,2,7,0,165.624,0.998693,0.997107,0.996958,0.997464,0.998269,1.03971 +-163.563,0.963315,0.114275,4,23,0,166.224,0.998722,0.997022,0.997504,0.997662,0.997675,1.03387 +-163.952,0.939382,0.114275,4,23,0,165.408,0.999037,0.998999,0.997473,0.998995,0.998827,0.991095 +-164.159,0.884297,0.114275,3,15,0,170.8,0.999898,0.999539,0.99942,1.00032,0.999352,1.01817 +-164.785,0.93166,0.114275,3,7,0,166.11,1.00103,0.99954,0.998831,0.99884,0.999579,1.01164 +-165.312,0.893712,0.114275,4,23,0,171.486,1.00079,0.999843,0.99997,0.999681,0.999555,1.18805 +-163.217,0.902498,0.114275,3,15,0,168.581,0.999392,0.998283,0.997743,0.998869,0.998646,1.12481 +-163.708,0.966006,0.114275,4,31,0,165.012,0.998402,0.997102,0.997363,0.998034,0.997578,1.06263 +-165.029,0.679903,0.114275,3,7,0,171.922,0.999122,0.998091,0.996207,0.99806,0.997757,1.11584 +-163.649,0.961914,0.114275,2,3,0,166.256,0.998347,0.997754,0.997035,0.997411,0.997704,1.11798 +-163.909,0.988197,0.114275,3,7,0,164.448,0.9986,0.997546,0.996614,0.997925,0.997095,1.11681 +-163.456,0.832281,0.114275,3,7,0,166.952,0.998295,0.997625,0.996713,0.997169,0.997484,1.08004 +-162.895,0.820172,0.114275,2,3,0,165.51,0.998453,0.997716,0.996823,0.997426,0.997467,1.06842 +-164.333,0.841331,0.114275,4,23,0,166.233,1.00063,0.999874,0.999151,1.00011,0.999067,1.15199 +-165.574,0.886188,0.114275,4,23,0,169.733,0.999552,1.00004,0.998241,0.999596,0.999392,0.953619 +-162.944,1,0.114275,2,3,0,165.708,1.00015,0.998884,0.998676,0.999512,0.998576,0.95319 +-163.909,0.884549,0.114275,4,27,0,166.184,1.00073,0.999691,0.999495,1.00045,1.0003,1.01529 +-162.129,0.996555,0.114275,3,15,0,164.521,0.999236,0.998343,0.997966,0.998419,0.99868,1.01163 +-166.091,0.671076,0.114275,3,15,0,168.865,1.00196,1.00033,0.999157,0.999905,0.99992,1.03848 +-164.369,1,0.114275,2,3,0,167.307,1.00086,0.999364,1.00023,1.00026,0.999892,1.04068 +-163.791,0.97163,0.114275,3,15,0,165.557,0.999626,0.99958,0.997916,0.999022,0.999262,1.0536 +-165.222,0.852372,0.114275,3,7,0,166.234,0.999601,0.998496,0.997906,0.998328,0.999558,1.04901 +-162.281,1,0.114275,2,3,0,165.385,0.99966,0.998404,0.998148,0.998736,0.998941,1.05108 +-167.364,0.619004,0.114275,3,7,0,168.414,0.999267,0.997804,0.998968,0.998483,0.999537,1.06336 +-167.596,0.997251,0.114275,3,15,0,171.535,1.00111,1.0009,0.998379,0.999843,0.999483,1.14585 +-167.535,0.891591,0.114275,3,7,0,170.997,0.999885,0.999508,0.998498,1.00004,1.00039,1.14613 +-169.674,0.915555,0.114275,2,7,0,170.981,0.999767,0.999651,0.998922,1.00003,1.00083,1.15486 +-164.334,1,0.114275,2,3,0,169.43,1.00069,0.999777,0.999047,1.00023,0.99987,1.15918 +-165.439,0.868347,0.114275,4,15,0,168.716,0.997242,0.996964,0.995774,0.996942,0.996573,1.12327 +-164.386,0.941855,0.114275,4,15,0,167.431,0.998585,0.996839,0.996657,0.997823,0.9978,1.04833 +-165.228,0.884088,0.114275,4,27,0,168.134,1.00093,0.998575,0.998614,0.999315,0.998926,1.15167 +-165.732,0.83087,0.114275,3,7,0,169.805,0.999509,0.998811,0.997391,0.999708,0.998507,1.15558 +-163.958,0.987676,0.114275,4,27,0,168.826,1.00021,0.999201,0.999389,0.998668,0.999373,1.04108 +-164.554,0.969486,0.114275,2,7,0,166.71,1.00009,0.999378,0.999947,1.00009,0.999842,1.04881 +-164.762,0.994685,0.114275,4,31,0,166.221,0.99952,0.997841,0.997751,0.997762,0.997705,1.16137 +-166.687,0.808863,0.114275,3,7,0,168.778,0.999086,0.998691,0.998029,1.00002,0.998928,1.13358 +-163.791,0.948304,0.114275,2,3,0,168.212,0.999987,0.998815,0.998643,0.998664,0.99868,1.16061 +-163.056,0.906219,0.114275,4,15,0,166.338,0.998784,0.998024,0.996818,0.998257,0.998056,1.06664 +-163.141,0.931673,0.114275,3,15,0,165.875,0.999377,0.998551,0.997914,0.998337,0.99784,1.11552 +-162.927,0.967131,0.114275,3,15,0,164.474,1.00022,0.999308,0.997995,0.99892,0.998504,1.03816 +-162.32,1,0.114275,3,15,0,163.721,0.999319,0.998896,0.998062,0.998477,0.998719,1.04544 +-165.975,0.618677,0.114275,3,15,0,171.386,1.0019,1.00035,1.00022,1.00081,0.999597,1.0618 +-164.807,0.979966,0.114275,3,15,0,167.442,0.99973,0.999338,0.998756,0.999217,1.00001,1.05718 +-164.482,1,0.114275,3,15,0,166.179,1.00009,0.998645,0.99809,0.999108,0.997792,1.09242 +-163.071,0.984336,0.114275,3,15,0,166.065,0.998613,0.998501,0.997808,0.998051,0.998137,1.06913 +-162.877,0.843421,0.114275,2,7,0,165.456,0.999327,0.997773,0.997852,0.9986,0.998433,1.07312 +-163.802,0.945019,0.114275,3,7,0,164.536,0.999002,0.999037,0.997293,0.998545,0.997914,1.09661 +-163.069,0.996784,0.114275,2,7,0,164.561,0.999068,0.99826,0.997037,0.997901,0.997863,1.10042 +-163.069,0.278837,0.114275,2,3,0,175.458,0.999068,0.99826,0.997037,0.997901,0.997863,1.10042 +-163.053,0.989244,0.114275,3,7,0,163.485,0.998714,0.997688,0.997785,0.998196,0.997791,1.09203 +-164.41,0.877556,0.114275,2,3,0,164.952,0.99903,0.997335,0.997665,0.998596,0.997606,1.09991 +-163.712,0.923494,0.114275,3,7,0,166.356,0.998706,0.998623,0.997242,0.998372,0.998308,1.11309 +-163.274,0.983743,0.114275,5,31,0,165.864,0.999451,0.997681,0.998141,0.997984,0.9983,1.05291 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0.096412 seconds (Sampling) +# 0.205319 seconds (Total) +# diff --git a/examples/sblrc-blr/1.output.csv b/examples/sblrc-blr/1.output.csv new file mode 100644 index 0000000000..f1cfa8d338 --- /dev/null +++ b/examples/sblrc-blr/1.output.csv @@ -0,0 +1,2058 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = sblrc_blr_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 1 +# data +# file = sblrc-blr.data.R +# init = 2 (Default) +# random +# seed = 1540963 +# output +# file = 1.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +-380568,1,0.000488281,1,1,0,3.42491e+06,0.774371,-0.721778,-1.01809,-1.30734,0.497616,4.90742 +-380568,0,14.3855,0,1,1,380571,0.774371,-0.721778,-1.01809,-1.30734,0.497616,4.90742 +-380568,0,2.43117,0,1,1,380569,0.774371,-0.721778,-1.01809,-1.30734,0.497616,4.90742 +-380568,0,0.239791,0,1,1,380569,0.774371,-0.721778,-1.01809,-1.30734,0.497616,4.90742 +-380568,0,0.0186273,0,1,1,380574,0.774371,-0.721778,-1.01809,-1.30734,0.497616,4.90742 +-74717.5,1,0.00130482,3,15,0,295863,0.604916,-0.668933,-0.905483,-1.11669,0.353398,9.39028 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+-168.833,0.99244,0.0713617,4,15,0,172.563,0.998003,0.998483,0.997113,0.998515,0.997962,0.869498 +-166.184,0.994079,0.116096,2,7,0,170.535,0.998834,0.998581,0.997166,0.998905,0.997908,0.878409 +-165.75,0.673345,0.188333,2,3,0,168.661,0.999148,0.99852,0.997087,0.999133,0.998004,0.904458 +-163.118,0.994877,0.141784,4,15,0,166.463,1.00079,0.999688,0.999022,0.999194,0.999372,0.987827 +# num_warmup = 1000 +# Adaptation terminated +# Step size = 0.12297 +# Elements of inverse mass matrix: +# 1.07966e-05, 7.37842e-07, 7.82982e-07, 7.50673e-07, 7.38756e-07, -1.73008e-06 +# 7.37842e-07, 1.0872e-05, 7.7998e-07, 7.90642e-07, 7.53841e-07, -1.49804e-06 +# 7.82982e-07, 7.7998e-07, 1.10156e-05, 8.31571e-07, 8.13432e-07, -2.37874e-06 +# 7.50673e-07, 7.90642e-07, 8.31571e-07, 1.08761e-05, 7.59112e-07, -1.10077e-06 +# 7.38756e-07, 7.53841e-07, 8.13432e-07, 7.59112e-07, 1.07975e-05, -2.28636e-06 +# -1.73008e-06, -1.49804e-06, -2.37874e-06, -1.10077e-06, -2.28636e-06, 0.00560556 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+-165.33,0.853871,0.12297,3,7,0,165.935,0.999855,0.998269,0.997907,0.99851,0.997769,0.892411 +-164.73,0.777677,0.12297,2,3,0,167.573,0.999322,0.998391,0.998624,0.99821,0.998503,0.898211 +# +# Elapsed Time: 0.11849 seconds (Warm-up) +# 0.089216 seconds (Sampling) +# 0.207706 seconds (Total) +# diff --git a/examples/sblrc-blr/2.output.csv b/examples/sblrc-blr/2.output.csv new file mode 100644 index 0000000000..645339ffe0 --- /dev/null +++ b/examples/sblrc-blr/2.output.csv @@ -0,0 +1,2058 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = sblrc_blr_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 2 +# data +# file = sblrc-blr.data.R +# init = 2 (Default) +# random +# seed = 1540963 +# output +# file = 2.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +-8911.37,1,0.00195312,1,1,0,220266,1.6666,1.10892,0.88952,1.47221,1.49343,11.1482 +-8911.37,0,14.3855,0,1,1,8912.36,1.6666,1.10892,0.88952,1.47221,1.49343,11.1482 +-8911.37,0,2.43117,0,1,1,8917.65,1.6666,1.10892,0.88952,1.47221,1.49343,11.1482 +-8911.37,0,0.239791,0,1,1,8911.57,1.6666,1.10892,0.88952,1.47221,1.49343,11.1482 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+-163.564,0.975233,0.0688846,4,31,0,167.196,0.998265,0.997674,0.997471,0.997606,0.997301,1.09371 +-165.973,0.895445,0.107677,4,15,0,168.046,1.00081,1.00009,1.00065,1.00103,1.00029,0.999982 +-166.184,0.829431,0.13805,2,3,0,169.668,1.00214,1.0006,1.00079,1.00141,1.00044,0.995505 +-167.76,0.721362,0.150641,2,3,0,168.784,1.00167,1.00128,0.999661,1.00086,1.00128,0.990356 +-169.904,0.897406,0.127037,3,7,0,170.968,1.00176,1.002,0.999822,1.00079,1.00123,0.992267 +# num_warmup = 1000 +# Adaptation terminated +# Step size = 0.112442 +# Elements of inverse mass matrix: +# 1.07812e-05, 6.59079e-07, 7.53731e-07, 7.31027e-07, 7.11588e-07, -5.87445e-06 +# 6.59079e-07, 1.08138e-05, 7.13338e-07, 7.25449e-07, 7.1257e-07, -4.51961e-06 +# 7.53731e-07, 7.13338e-07, 1.09978e-05, 7.95116e-07, 8.09809e-07, -6.46015e-06 +# 7.31027e-07, 7.25449e-07, 7.95116e-07, 1.08326e-05, 7.43673e-07, -6.52372e-06 +# 7.11588e-07, 7.1257e-07, 8.09809e-07, 7.43673e-07, 1.08123e-05, -6.71553e-06 +# -5.87445e-06, -4.51961e-06, -6.46015e-06, -6.52372e-06, -6.71553e-06, 0.00458952 +-168.563,1,0.112442,3,7,0,170.758,1.00195,1.00001,1.00137,1.00147,1.0005,1.01774 +-168.057,0.935842,0.112442,3,7,0,171.977,1.00142,0.99986,1.00076,1.00099,1.0013,1.005 +-164.491,0.994503,0.112442,2,3,0,168.642,1.00156,1.0005,1.00042,1.00089,1.00079,1.00167 +-163.556,0.846364,0.112442,3,7,0,166.093,1.00116,1.00054,0.999856,1.00067,1.00033,1.02271 +-165.868,0.772659,0.112442,3,15,0,168.261,0.999833,1.00007,1.00022,0.999992,0.999557,1.04004 +-163.921,0.991291,0.112442,3,15,0,167.755,1.0006,0.998892,0.998209,0.999806,0.999256,0.976953 +-166.42,0.86846,0.112442,4,31,0,168.91,0.997999,0.997697,0.998128,0.998311,0.997718,1.16116 +-165.597,0.955904,0.112442,3,7,0,168.141,0.999212,0.997786,0.996368,0.997997,0.998035,1.16677 +-163.996,0.955615,0.112442,4,31,0,169.931,1.00101,0.999256,0.999831,0.99982,0.999275,1.05282 +-164.159,0.849644,0.112442,3,7,0,167.338,0.999864,0.999867,0.999749,0.999934,0.999502,1.05398 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b/examples/sblrc-blr/3.output.csv @@ -0,0 +1,2058 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = sblrc_blr_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 3 +# data +# file = sblrc-blr.data.R +# init = 2 (Default) +# random +# seed = 1540963 +# output +# file = 3.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +-1.13526e+07,1,6.10352e-05,1,1,0,4.01318e+08,-0.813616,-1.62017,-1.72602,-1.22789,-1.30818,0.62645 +-1.13526e+07,0,14.3855,0,1,1,1.13526e+07,-0.813616,-1.62017,-1.72602,-1.22789,-1.30818,0.62645 +-1.13526e+07,0,2.43117,0,1,1,1.13526e+07,-0.813616,-1.62017,-1.72602,-1.22789,-1.30818,0.62645 +-1.13526e+07,0,0.239791,0,1,1,1.13526e+07,-0.813616,-1.62017,-1.72602,-1.22789,-1.30818,0.62645 +-1.13526e+07,0,0.0186273,0,1,1,1.13526e+07,-0.813616,-1.62017,-1.72602,-1.22789,-1.30818,0.62645 +-1.13526e+07,0,0.00130482,0,1,1,1.13526e+07,-0.813616,-1.62017,-1.72602,-1.22789,-1.30818,0.62645 +-9.27488e+06,1,8.85015e-05,1,1,0,1.1167e+07,-0.830082,-1.59914,-1.70925,-1.23007,-1.29804,0.684632 +-6.29253e+06,1,0.000135987,1,1,0,8.8229e+06,-0.860406,-1.559,-1.67683,-1.23371,-1.27896,0.812632 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+-167.11,0.898339,0.0873895,2,3,0,167.929,0.999106,0.998336,0.998615,0.999531,0.999621,1.01396 +-163.466,1,0.118201,2,3,0,167.802,1.00066,0.999572,0.99834,0.999243,0.998721,1.03285 +-163.594,0.655019,0.209665,3,11,0,165.63,0.999946,0.999726,0.997988,0.999205,0.99896,1.09682 +-163.895,0.882139,0.145466,4,23,0,165.622,1.00017,0.999223,0.99858,0.999912,0.998441,0.984516 +-164.397,0.451119,0.186253,3,15,0,169.655,1.00058,0.999482,0.998404,0.999115,0.999946,1.03693 +-163.458,0.996792,0.0757817,5,31,0,168.074,0.999433,0.999285,0.998371,0.999337,0.998588,0.926337 +-165.172,0.642519,0.131317,2,3,0,166.854,1.00051,0.999182,0.998404,0.998485,0.99869,0.924662 +-167.246,0.905419,0.0895187,3,7,0,170.11,0.99909,0.999212,0.998906,0.999245,0.999491,0.904779 +-163.932,1,0.121224,3,11,0,167.868,0.998826,0.997801,0.99686,0.99806,0.998222,0.9354 +-166.359,0.587045,0.208305,3,15,0,168.222,0.999,0.99669,0.997493,0.99742,0.998257,1.00029 +-165.211,0.921647,0.123893,3,11,0,169.26,0.9993,0.999728,0.998156,0.999221,0.997998,0.996312 +-164.881,0.920664,0.173128,2,7,0,167.568,1.0004,0.998416,0.997869,0.999055,0.999431,0.980154 +-163.544,0.0858093,0.240109,3,15,0,167.876,0.999216,0.997549,0.997129,0.997859,0.997598,1.11543 +-164.691,0.984873,0.0413593,4,31,0,166.525,0.999232,0.998922,0.997482,0.998117,0.997576,1.13513 +-163.5,0.999554,0.0676042,3,7,0,165.444,0.999263,0.998301,0.997553,0.997905,0.997862,1.13613 +-165.552,1,0.113739,4,15,0,166.109,0.999857,0.999072,0.998467,0.99904,0.999102,1.24387 +-164.21,0.749342,0.190133,4,15,0,168.526,1.00055,0.99878,0.999619,0.999644,0.998972,1.07156 +-163.181,0.715947,0.171925,2,3,0,166.361,0.999461,0.99959,0.99867,0.999372,0.998918,1.07361 +-165.203,0.67039,0.143646,3,7,0,167.798,1.00108,1.00065,0.998715,1.00051,0.999607,1.04661 +-163.4,0.987845,0.107895,3,7,0,166.185,1.00096,0.999492,0.999219,1.0003,0.99932,1.0498 +-164.618,0.869137,0.172777,4,15,0,166.473,1.00134,1.00056,1.00014,1.00014,1.00066,1.00417 +# num_warmup = 1000 +# Adaptation terminated +# Step size = 0.12948 +# Elements of inverse mass matrix: +# 1.08058e-05, 7.27889e-07, 7.94114e-07, 7.49773e-07, 7.56557e-07, -1.7778e-06 +# 7.27889e-07, 1.08921e-05, 8.11903e-07, 7.88949e-07, 7.70371e-07, -4.31245e-06 +# 7.94114e-07, 8.11903e-07, 1.09943e-05, 8.03253e-07, 8.1618e-07, -9.76038e-07 +# 7.49773e-07, 7.88949e-07, 8.03253e-07, 1.08493e-05, 7.43291e-07, -2.0672e-06 +# 7.56557e-07, 7.70371e-07, 8.1618e-07, 7.43291e-07, 1.08216e-05, -1.43392e-06 +# -1.7778e-06, -4.31245e-06, -9.76038e-07, -2.0672e-06, -1.43392e-06, 0.00515843 +-164.359,0.706821,0.12948,3,15,0,168.235,0.998862,0.998379,0.997722,0.998682,0.999087,1.03988 +-162.4,0.923328,0.12948,2,3,0,165.628,0.999385,0.998068,0.997543,0.998825,0.998225,1.02944 +-162.451,0.980581,0.12948,3,7,0,163.305,0.999853,0.999235,0.998717,0.998689,0.998978,1.02861 +-162.336,0.991655,0.12948,3,15,0,165.322,0.999041,0.997629,0.997586,0.998209,0.997886,1.03093 +-163.101,0.505492,0.12948,2,7,0,169.216,0.999862,0.998917,0.997373,0.998568,0.998565,1.007 +-164.107,0.933084,0.12948,3,11,0,165.651,0.999998,0.999265,0.99987,0.999804,0.999216,1.0186 +-164.765,0.943745,0.12948,3,7,0,166.275,1.00133,0.999985,0.998864,1.00068,1.00001,1.03223 +-163.304,0.998765,0.12948,3,15,0,165.628,0.999606,0.999113,0.999189,0.99874,0.998773,1.03888 +-162.616,0.560993,0.12948,3,15,0,170.495,0.998933,0.997397,0.997251,0.997869,0.997853,1.03068 +-165.968,0.525577,0.12948,3,7,0,168.344,0.999653,0.997754,0.997971,0.999402,0.999202,1.06333 +-164.264,0.986925,0.12948,3,7,0,167.05,1.00023,0.999721,0.998712,0.998544,0.998815,1.04934 +-163.572,0.998299,0.12948,3,7,0,164.968,1.00025,0.999071,0.999038,1.00025,0.999299,1.03505 +-162.944,0.79295,0.12948,3,7,0,166.769,0.999584,0.998705,0.998848,0.999509,0.998642,1.01799 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+-164.644,0.77437,0.12948,3,7,0,167.617,1.00135,1.00075,0.999742,1.00007,0.999642,1.038 +-166.935,0.863328,0.12948,3,15,0,169.226,1.00099,0.999657,1.00075,1.00075,1.00072,1.00541 +-167.632,0.992426,0.12948,2,7,0,170.87,1.00254,1.00101,1.00139,1.0014,1.0006,1.00769 +-164.422,0.642342,0.12948,3,15,0,174.878,0.998052,0.996519,0.996455,0.997044,0.996585,1.06336 +# +# Elapsed Time: 0.103868 seconds (Warm-up) +# 0.087073 seconds (Sampling) +# 0.190941 seconds (Total) +# diff --git a/examples/sblrc-blr/cross_chain_summary.R b/examples/sblrc-blr/cross_chain_summary.R new file mode 100644 index 0000000000..0e5341dcff --- /dev/null +++ b/examples/sblrc-blr/cross_chain_summary.R @@ -0,0 +1,44 @@ +cc.summary <- function(stanfit) { + +(n_warmup = stanfit@sim$warmup) +n_iter = stanfit@sim$iter-n_warmup +sampler_params <- rstan:::get_sampler_params(stanfit, inc_warmup = TRUE) +leapfrogs = sapply(sampler_params, function(x) x[, "n_leapfrog__"]) +(sum_warmup_leapfrogs = sum(leapfrogs[1:n_warmup,])) +(sum_leapfrogs = sum(leapfrogs[n_warmup+(1:n_iter),])) +(mean_warmup_leapfrogs = sum_warmup_leapfrogs/n_warmup) +(mean_leapfrogs = sum_leapfrogs/n_iter) +mon = rstan::monitor(as.array(stanfit), warmup=0, print=FALSE) +(maxrhat = max(mon[,'Rhat'])) +bulk_ess_per_iter = mon[,'Bulk_ESS']/n_iter +tail_ess_per_iter = mon[,'Tail_ESS']/n_iter +bulk_ess_per_leapfrog = mon[,'Bulk_ESS']/sum_leapfrogs +tail_ess_per_leapfrog = mon[,'Tail_ESS']/sum_leapfrogs +min(bulk_ess_per_iter) +min(tail_ess_per_iter) +min(bulk_ess_per_leapfrog) +min(tail_ess_per_leapfrog) +(stepsizes = sapply(sampler_params, function(x) x[, "stepsize__"])[n_iter,]) + +## classic warmup +(n_warmup = stanfit@sim$warmup) +n_iter = stanfit@sim$iter-n_warmup +sampler_params <- rstan:::get_sampler_params(stanfit, inc_warmup = TRUE) +leapfrogs = sapply(sampler_params, function(x) x[, "n_leapfrog__"]) +(sum_warmup_leapfrogs = sum(leapfrogs[1:n_warmup,])) +(sum_leapfrogs = sum(leapfrogs[n_warmup+(1:n_iter),])) +(mean_warmup_leapfrogs = sum_warmup_leapfrogs/n_warmup) +(mean_leapfrogs = sum_leapfrogs/n_iter) +mon = rstan::monitor(as.array(stanfit), warmup=0, print=FALSE) +(maxrhat = max(mon[,'Rhat'])) +bulk_ess_per_iter = mon[,'Bulk_ESS']/n_iter +tail_ess_per_iter = mon[,'Tail_ESS']/n_iter +bulk_ess_per_leapfrog = mon[,'Bulk_ESS']/sum_leapfrogs +tail_ess_per_leapfrog = mon[,'Tail_ESS']/sum_leapfrogs +min(bulk_ess_per_iter) +min(tail_ess_per_iter) +min(bulk_ess_per_leapfrog) +min(tail_ess_per_leapfrog) +(stepsizes = sapply(sampler_params, function(x) x[, "stepsize__"])[n_iter,]) + +} diff --git a/examples/sblrc-blr/mpi.0.output.csv b/examples/sblrc-blr/mpi.0.output.csv new file mode 100644 index 0000000000..ba3d514d27 --- /dev/null +++ b/examples/sblrc-blr/mpi.0.output.csv @@ -0,0 +1,1408 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = sblrc_blr_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 0 (Default) +# data +# file = sblrc-blr.data.R +# init = 2 (Default) +# random +# seed = 1540963 +# output +# file = mpi.0.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,beta.1,beta.2,beta.3,beta.4,beta.5,sigma 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+-163.93,0.958158,0.109463,3,15,0,165.569,1.0002,0.999838,0.999482,0.999095,0.999701,1.02528 +-165.578,0.878756,0.144411,3,15,0,167.451,1.00028,0.998026,0.999184,0.999622,0.998959,1.00741 +-165.761,0.961146,0.166483,3,7,0,168.874,1.00161,0.999945,0.999562,1.00126,1.00016,1.05375 +-167.881,0.598405,0.219973,4,15,0,171.223,1.00025,0.997367,0.997634,0.998927,0.998173,1.19657 +-164.73,1,0.158743,3,7,0,168.87,0.999542,0.999287,0.998605,0.999017,0.99841,1.19014 +-167.953,0.726489,0.223285,2,3,0,169.25,1.00103,0.998837,0.999415,0.99928,0.999435,1.27519 +-165.114,0.726483,0.199491,3,11,0,173.108,0.998785,0.997344,0.99588,0.997776,0.997388,0.997726 +-165.067,0.847438,0.178362,2,3,0,167.319,0.998202,0.99758,0.996679,0.996593,0.996897,1.00168 +-164.14,0.945474,0.194592,2,7,0,167.145,0.999593,0.998253,0.998011,0.999609,0.998644,1.08698 +-165.506,0.957759,0.249036,2,7,0,166.066,0.998845,0.998573,0.997687,0.997331,0.997782,1.1487 +-165.506,0.146551,0.324615,2,7,0,171.446,0.998845,0.998573,0.997687,0.997331,0.997782,1.1487 +-164.627,0.996275,0.113176,3,7,0,166.35,0.9994,0.997975,0.997625,0.999356,0.998577,1.10373 +-164.395,0.896389,0.157134,3,7,0,169.094,0.999756,0.998773,0.996892,0.998861,0.998248,1.0778 +-163.967,0.836403,0.185303,2,3,0,167.276,0.999269,0.999313,0.99751,0.998881,0.998934,1.0541 +-162.349,1,0.198214,2,7,0,164.675,1.00024,0.999009,0.998044,0.998971,0.998912,1.0423 +-162.349,0.0917572,0.275456,2,3,0,164.587,1.00024,0.999009,0.998044,0.998971,0.998912,1.0423 +-162.353,0.997952,0.0895191,3,15,0,163.61,1.00027,0.998994,0.998373,0.999002,0.998738,1.07213 +-166.027,0.823194,0.124045,2,3,0,166.349,0.999446,1.00027,0.998128,0.999829,0.998858,1.07852 +-169.412,0.959317,0.129974,3,7,0,170.939,1.00273,1.00009,1.00144,1.00069,1.00102,1.09219 +-169.068,0.829389,0.168869,4,15,0,174.794,0.997269,0.997678,0.995265,0.996399,0.995796,1.05036 +-168.696,0.759788,0.178445,3,7,0,174.272,0.996236,0.996408,0.995149,0.995505,0.995876,1.04681 +-163.418,1,0.168951,3,11,0,170.372,1.00076,0.998964,0.998903,0.99913,0.999354,1.09648 +-162.332,0.547107,0.233196,2,7,0,165.762,0.999201,0.998993,0.998173,0.999074,0.998491,1.02497 +-164.915,0.742266,0.158256,3,7,0,167.502,1.00166,0.999925,0.999561,0.999797,1.00042,1.04465 +-166.236,0.93486,0.145915,3,7,0,168.744,1.00161,1.00083,1.00085,1.00118,0.999897,1.06152 +-165.422,0.663952,0.18155,2,3,0,170.392,1.00179,1.00083,0.999968,1.0007,1.00099,1.10442 +-164.953,0.944523,0.148271,3,7,0,167.633,1.0019,1.00007,1.00008,1.00055,1.00066,1.08602 +-166.034,0.821061,0.186994,4,15,0,171.459,0.99853,0.996385,0.996886,0.996584,0.997325,1.02475 +-164.689,0.990593,0.194725,4,15,0,167.293,1.00142,0.999973,1.00035,1.00082,1.00031,1.10567 +-165.94,0.444631,0.262997,3,7,0,168.377,0.998437,0.998107,0.997703,0.997128,0.998429,1.05925 +# num_warmup = 350 +# Adaptation terminated +# Step size = 0.153713 +# Elements of inverse mass matrix: +# 7.1903e-06, 7.25058e-07, 8.75532e-07, 8.11132e-07, 8.11523e-07, -4.02963e-07 +# 7.25058e-07, 7.20145e-06, 8.29458e-07, 7.72194e-07, 7.73772e-07, 1.59025e-06 +# 8.75532e-07, 8.29458e-07, 7.49649e-06, 9.20819e-07, 9.07225e-07, 2.88878e-07 +# 8.11132e-07, 7.72194e-07, 9.20819e-07, 7.25458e-06, 8.22173e-07, -5.14298e-06 +# 8.11523e-07, 7.73772e-07, 9.07225e-07, 8.22173e-07, 7.20964e-06, -4.1653e-06 +# -4.02963e-07, 1.59025e-06, 2.88878e-07, -5.14298e-06, -4.1653e-06, 0.0137105 +-163.01,0.822763,0.153713,2,7,0,169.708,0.999291,0.997724,0.997334,0.998304,0.99844,1.05804 +-163.655,0.969972,0.153713,3,7,0,165.262,0.998247,0.997266,0.997235,0.997232,0.996986,1.04342 +-164.152,0.939866,0.153713,3,7,0,165.009,0.998372,0.99738,0.995932,0.997394,0.997341,1.06311 +-164.256,0.996253,0.153713,4,15,0,165.587,1.00137,1.00043,0.999462,1.0009,0.999873,1.05221 +-162.805,1,0.153713,2,3,0,164.309,1.00076,0.999945,0.999543,0.999898,0.999964,1.05436 +-161.669,0.996914,0.153713,3,11,0,163.765,0.999391,0.998468,0.997823,0.998665,0.998221,1.00593 +-162.439,0.748577,0.153713,3,7,0,164.357,0.998893,0.998412,0.997178,0.998302,0.997945,0.976574 +-164.573,0.777274,0.153713,3,11,0,165.603,1.00052,0.998338,0.999027,0.998556,0.998766,1.05547 +-164.13,1,0.153713,3,7,0,165.325,0.999007,0.998667,0.99713,0.999049,0.997816,1.08045 +-169.257,0.785343,0.153713,3,7,0,171.62,1.00146,1.00027,1.00176,1.00145,1.00108,1.04893 +-168.41,0.971067,0.153713,3,7,0,172.498,1.00206,1.00014,1.00105,1.00023,1.00138,1.08023 +-166.075,1,0.153713,2,3,0,169.627,1.00151,1,1.00071,1.00119,1,1.05748 +-168.179,0.744329,0.153713,2,7,0,171.607,1.00204,1.00036,0.998592,1.00073,0.999747,1.05406 +-170.88,0.708725,0.153713,3,7,0,174.468,0.99846,0.998725,0.999352,0.998568,0.999634,1.0347 +-163.615,1,0.153713,2,3,0,171.899,0.999815,0.999728,0.999286,0.999167,0.998791,1.03799 +-163.62,0.915007,0.153713,3,15,0,166.187,1.00011,0.998192,0.998068,0.998994,0.99912,0.975465 +-163.93,0.944793,0.153713,3,7,0,165.274,0.998689,0.997976,0.997318,0.998841,0.998285,0.978133 +-164.155,0.829003,0.153713,2,3,0,167.146,0.998869,0.998127,0.997332,0.997283,0.997261,1.00422 +-164.028,0.978339,0.153713,4,15,0,167.533,0.999811,0.998982,0.998654,1.00001,0.999388,0.974644 +-163.825,0.998045,0.153713,4,15,0,165.356,0.999085,0.998593,0.997619,0.997643,0.997671,0.98731 +-163.521,0.599213,0.153713,3,7,0,171.209,0.998721,0.997464,0.996869,0.997821,0.997224,1.11437 +-163.446,0.91351,0.153713,4,15,0,168.858,0.998222,0.997168,0.997128,0.997246,0.997383,0.980897 +-164.646,0.823157,0.153713,4,15,0,166.202,0.999075,0.998354,0.996821,0.997609,0.997906,0.9297 +-162.752,0.932088,0.153713,2,3,0,165.327,0.998877,0.997981,0.997501,0.99807,0.997838,0.926379 +-163.496,0.889377,0.153713,2,3,0,163.71,0.999021,0.99781,0.997524,0.997705,0.99765,0.922455 +-163.649,0.908422,0.153713,3,7,0,164.507,0.998895,0.997738,0.997391,0.998471,0.998341,0.938934 +-163.698,0.911244,0.153713,2,3,0,165.384,0.99925,0.998082,0.997704,0.99769,0.998401,0.944162 +-163.704,1,0.153713,4,15,0,164.671,0.999994,0.999879,0.998566,0.999131,0.999382,1.10209 +-162.422,1,0.153713,4,15,0,164.458,0.998818,0.998349,0.997332,0.998235,0.997611,1.03314 +-162.686,0.948769,0.153713,4,15,0,163.794,1,0.998773,0.9978,0.9991,0.998899,0.964736 +-168.377,0.453854,0.153713,3,11,0,174.336,1.00071,0.999966,0.999489,1.00107,0.999127,1.23511 +-171.925,0.902411,0.153713,4,15,0,176.134,0.999024,0.998297,0.998048,0.997457,0.998789,0.824613 +-163.608,0.976536,0.153713,4,15,0,173.452,0.998297,0.997657,0.996455,0.99747,0.997663,0.973492 +-165.196,0.91911,0.153713,2,3,0,165.896,0.998945,0.997036,0.996947,0.997118,0.997116,0.945643 +-163.524,1,0.153713,2,3,0,166.046,0.998438,0.997786,0.997397,0.998349,0.997536,0.950764 +-162.666,0.990686,0.153713,3,7,0,165.749,0.999261,0.997966,0.997523,0.998605,0.997774,0.973209 +-164.26,0.894287,0.153713,3,15,0,167.655,0.999449,0.998892,0.998413,0.998627,0.999047,1.17043 +-165.09,0.863922,0.153713,3,15,0,169.133,0.997988,0.998056,0.997379,0.997736,0.997963,0.939026 +-165.06,1,0.153713,2,3,0,166.525,0.999227,0.997228,0.996985,0.997797,0.997313,0.926966 +-165.812,0.891967,0.153713,4,15,0,168.366,1.00014,0.997833,0.997811,0.998891,0.998197,0.915157 +-164.235,0.990677,0.153713,3,15,0,168.379,1.00116,1.00048,1.00003,1.00034,0.999537,1.07041 +-163.869,0.953302,0.153713,2,3,0,165.259,1.00075,1.00045,0.999452,1.00052,0.999522,1.07393 +-167.252,0.809853,0.153713,3,7,0,168.889,1.00254,1.00026,1.00027,1.00092,1.00121,1.06229 +-163.1,0.927122,0.153713,4,15,0,168.823,0.99995,0.998205,0.997924,0.998514,0.999,1.01917 +-162.458,0.983787,0.153713,3,15,0,164.889,1.00015,0.998886,0.99814,0.998604,0.99884,1.04313 +-163.898,0.94519,0.153713,4,15,0,166.355,1.0011,1.00015,1.00023,1.00065,1.00046,1.02791 +-166.562,0.72861,0.153713,4,15,0,169.388,1.00006,0.998439,0.997239,0.999258,0.998883,1.20197 +-166.635,0.85487,0.153713,3,15,0,170.66,0.9996,0.998786,0.999514,1.00002,0.998427,1.02193 +-163.482,1,0.153713,2,7,0,167.041,0.999802,0.999595,0.99828,0.999063,0.999496,1.04005 +-165.562,0.983773,0.153713,3,11,0,166.921,0.999342,0.997521,0.998004,0.998484,0.997445,1.16057 +-167.615,0.853526,0.153713,3,7,0,170.377,0.998821,0.998611,0.996626,0.997839,0.998453,1.23434 +-163.785,0.986746,0.153713,4,15,0,167.929,1.0006,1.00006,0.998745,1.00025,0.99957,0.955785 +-163.854,0.952041,0.153713,3,7,0,165.228,1.00102,0.999645,0.999849,0.99979,0.999854,0.944196 +-163.784,0.967594,0.153713,3,7,0,165.277,1.00046,0.999303,0.999579,0.999428,0.99979,0.945371 +-162.888,0.997093,0.153713,4,15,0,164.238,0.999561,0.998312,0.998683,0.998506,0.998925,1.0238 +-163.03,0.830883,0.153713,2,7,0,166.225,0.999878,0.999579,0.998785,0.999703,0.998645,0.992737 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+-164.332,0.980981,0.153713,3,7,0,170.455,1.00065,1.00019,0.998847,0.999661,1.0002,1.02586 +-164.94,0.972755,0.153713,4,15,0,166.394,0.998949,0.9985,0.997417,0.998907,0.997275,0.981074 +-167.809,0.936342,0.153713,2,7,0,173.186,0.999277,0.997319,0.996361,0.997856,0.997978,0.888449 +# +# Elapsed Time: 0.034787 seconds (Warm-up) +# 0.098101 seconds (Sampling) +# 0.132888 seconds (Total) +# diff --git a/examples/sblrc-blr/mpi.1.output.csv b/examples/sblrc-blr/mpi.1.output.csv new file mode 100644 index 0000000000..9d19fc97a2 --- /dev/null +++ b/examples/sblrc-blr/mpi.1.output.csv @@ -0,0 +1,1408 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = sblrc_blr_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 1 +# data +# file = sblrc-blr.data.R +# init = 2 (Default) +# random +# seed = 1540963 +# output +# file = mpi.1.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +-380568,1,0.000488281,1,1,0,3.42491e+06,0.774371,-0.721778,-1.01809,-1.30734,0.497616,4.90742 +-380568,0,14.3855,0,1,1,380571,0.774371,-0.721778,-1.01809,-1.30734,0.497616,4.90742 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+-162.664,0.678416,0.226228,2,7,0,168.655,1.0004,0.998963,0.998782,0.999105,0.999175,0.944043 +-163.409,0.748793,0.187095,2,3,0,164.486,0.999912,0.999367,0.998728,0.999709,0.998582,0.946831 +-163.531,0.602027,0.173412,2,3,0,167.76,1.00024,0.998766,0.998197,0.998448,0.998631,0.940914 +-165.276,0.816444,0.127196,4,15,0,169.194,1.00132,1.00052,0.999673,1.00021,1.00089,1.07975 +-163.566,0.994198,0.131523,4,15,0,166.611,0.999716,0.998628,0.998131,0.998035,0.998832,1.0897 +-163.485,0.978672,0.180292,2,3,0,164.452,0.999772,0.99894,0.998508,0.999839,0.99864,1.08705 +-163.638,0.82073,0.240668,2,7,0,166.82,0.999625,0.998182,0.997703,0.998717,0.999149,1.03746 +-164.981,0.342167,0.249954,2,5,0,167.161,0.999284,0.998945,0.998141,0.998981,0.999629,1.00951 +-163.827,0.997311,0.122269,3,15,0,166.709,1.00033,0.999113,0.998726,0.998845,0.998651,1.14284 +-164.528,0.704887,0.167797,2,3,0,167.318,0.99947,0.99902,0.998919,0.999617,0.999201,1.15198 +-164.066,0.918172,0.145509,3,15,0,168.669,1.00027,0.999174,0.997698,0.998591,0.99831,0.99935 +-162.117,1,0.176083,3,7,0,166.221,0.999482,0.998046,0.997804,0.998239,0.998025,1.00017 +-166.551,0.627878,0.241688,3,7,0,166.988,0.998769,0.998908,0.997677,0.998175,0.997725,0.871197 +-166.986,0.708052,0.186041,3,15,0,172.197,1.00009,1.00094,0.998939,1.00016,0.999734,0.96549 +-165.235,0.883417,0.162335,4,15,0,171.181,1.00106,1.00044,0.999338,0.99984,1.00042,1.13946 +-163.485,0.976763,0.185712,3,7,0,166.347,1.0001,0.998684,0.998654,0.999668,0.999056,1.11984 +-164.301,0.527373,0.244997,2,3,0,166.406,1.00037,0.998885,0.998592,0.99891,0.998115,1.10102 +# num_warmup = 350 +# Adaptation terminated +# Step size = 0.162175 +# Elements of inverse mass matrix: +# 7.1903e-06, 7.25058e-07, 8.75532e-07, 8.11132e-07, 8.11523e-07, -4.02963e-07 +# 7.25058e-07, 7.20145e-06, 8.29458e-07, 7.72194e-07, 7.73772e-07, 1.59025e-06 +# 8.75532e-07, 8.29458e-07, 7.49649e-06, 9.20819e-07, 9.07225e-07, 2.88878e-07 +# 8.11132e-07, 7.72194e-07, 9.20819e-07, 7.25458e-06, 8.22173e-07, -5.14298e-06 +# 8.11523e-07, 7.73772e-07, 9.07225e-07, 8.22173e-07, 7.20964e-06, -4.1653e-06 +# -4.02963e-07, 1.59025e-06, 2.88878e-07, -5.14298e-06, -4.1653e-06, 0.0137105 +-163.596,0.793465,0.162175,2,7,0,168.578,1.0007,0.998937,0.999455,0.999742,0.999017,1.03406 +-164.799,0.877586,0.162175,3,7,0,165.9,1.00082,0.99911,0.998198,0.999476,0.998445,0.992705 +-165.636,0.966814,0.162175,2,3,0,167.569,0.99931,0.999609,0.999171,0.999314,0.999629,0.970751 +-166.32,0.615675,0.162175,3,11,0,171.425,0.999711,0.999261,0.999661,0.999154,1.00002,1.13066 +-163.838,0.850608,0.162175,3,7,0,170.19,0.998809,0.997835,0.997988,0.998214,0.998749,1.02963 +-164.08,0.887843,0.162175,3,15,0,167.11,0.998814,0.998879,0.997297,0.998637,0.998258,0.93731 +-163.498,0.793576,0.162175,3,7,0,166.445,1.00023,0.998247,0.998589,0.998623,0.998351,1.00568 +-165.673,0.617169,0.162175,2,7,0,169.365,1.00062,0.999861,0.997612,0.999151,0.998817,1.05585 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+-162.854,0.715748,0.162175,3,11,0,166.243,0.9989,0.997667,0.998011,0.998059,0.998134,0.997564 +# +# Elapsed Time: 0.034422 seconds (Warm-up) +# 0.095712 seconds (Sampling) +# 0.130134 seconds (Total) +# diff --git a/examples/sblrc-blr/mpi.2.output.csv b/examples/sblrc-blr/mpi.2.output.csv new file mode 100644 index 0000000000..6a1b86ad03 --- /dev/null +++ b/examples/sblrc-blr/mpi.2.output.csv @@ -0,0 +1,1408 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = sblrc_blr_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 2 +# data +# file = sblrc-blr.data.R +# init = 2 (Default) +# random +# seed = 1540963 +# output +# file = mpi.2.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +-8911.37,1,0.00195312,1,1,0,220266,1.6666,1.10892,0.88952,1.47221,1.49343,11.1482 +-8911.37,0,14.3855,0,1,1,8912.36,1.6666,1.10892,0.88952,1.47221,1.49343,11.1482 +-8911.37,0,2.43117,0,1,1,8917.65,1.6666,1.10892,0.88952,1.47221,1.49343,11.1482 +-8911.37,0,0.239791,0,1,1,8911.57,1.6666,1.10892,0.88952,1.47221,1.49343,11.1482 +-8911.37,0,0.0186273,0,1,1,8914.34,1.6666,1.10892,0.88952,1.47221,1.49343,11.1482 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+-163.913,0.246295,0.315272,3,7,0,165.582,0.999721,0.999174,0.998417,0.998717,0.998019,1.1147 +-166.29,0.831563,0.134627,3,7,0,168.474,0.999303,0.9991,0.997927,0.999701,0.99765,1.09843 +-166.423,0.987357,0.14229,3,7,0,168.534,0.999691,0.998087,0.998272,0.997604,0.999197,1.0215 +-161.983,1,0.190966,2,3,0,165.907,0.999527,0.998282,0.997781,0.998216,0.998173,1.02544 +# num_warmup = 350 +# Adaptation terminated +# Step size = 0.260849 +# Elements of inverse mass matrix: +# 7.1903e-06, 7.25058e-07, 8.75532e-07, 8.11132e-07, 8.11523e-07, -4.02963e-07 +# 7.25058e-07, 7.20145e-06, 8.29458e-07, 7.72194e-07, 7.73772e-07, 1.59025e-06 +# 8.75532e-07, 8.29458e-07, 7.49649e-06, 9.20819e-07, 9.07225e-07, 2.88878e-07 +# 8.11132e-07, 7.72194e-07, 9.20819e-07, 7.25458e-06, 8.22173e-07, -5.14298e-06 +# 8.11523e-07, 7.73772e-07, 9.07225e-07, 8.22173e-07, 7.20964e-06, -4.1653e-06 +# -4.02963e-07, 1.59025e-06, 2.88878e-07, -5.14298e-06, -4.1653e-06, 0.0137105 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b/examples/sblrc-blr/mpi.3.output.csv new file mode 100644 index 0000000000..7797591098 --- /dev/null +++ b/examples/sblrc-blr/mpi.3.output.csv @@ -0,0 +1,1408 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = sblrc_blr_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 3 +# data +# file = sblrc-blr.data.R +# init = 2 (Default) +# random +# seed = 1540963 +# output +# file = mpi.3.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,beta.1,beta.2,beta.3,beta.4,beta.5,sigma +-1.13526e+07,1,6.10352e-05,1,1,0,4.01318e+08,-0.813616,-1.62017,-1.72602,-1.22789,-1.30818,0.62645 +-1.13526e+07,0,14.3855,0,1,1,1.13526e+07,-0.813616,-1.62017,-1.72602,-1.22789,-1.30818,0.62645 +-1.13526e+07,0,2.43117,0,1,1,1.13526e+07,-0.813616,-1.62017,-1.72602,-1.22789,-1.30818,0.62645 +-1.13526e+07,0,0.239791,0,1,1,1.13526e+07,-0.813616,-1.62017,-1.72602,-1.22789,-1.30818,0.62645 +-1.13526e+07,0,0.0186273,0,1,1,1.13526e+07,-0.813616,-1.62017,-1.72602,-1.22789,-1.30818,0.62645 +-1.13526e+07,0,0.00130482,0,1,1,1.13526e+07,-0.813616,-1.62017,-1.72602,-1.22789,-1.30818,0.62645 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+-164.783,0.604533,0.16092,2,3,0,170.651,0.999219,0.998973,0.999024,0.998588,0.999249,0.983528 +-163.356,1,0.119814,3,15,0,165.629,1,0.999007,0.997679,0.99933,0.998591,1.09771 +-163.112,0.966527,0.164005,3,11,0,165.341,1.00006,0.998789,0.999284,0.999432,0.999103,0.963827 +# num_warmup = 350 +# Adaptation terminated +# Step size = 0.212886 +# Elements of inverse mass matrix: +# 7.1903e-06, 7.25058e-07, 8.75532e-07, 8.11132e-07, 8.11523e-07, -4.02963e-07 +# 7.25058e-07, 7.20145e-06, 8.29458e-07, 7.72194e-07, 7.73772e-07, 1.59025e-06 +# 8.75532e-07, 8.29458e-07, 7.49649e-06, 9.20819e-07, 9.07225e-07, 2.88878e-07 +# 8.11132e-07, 7.72194e-07, 9.20819e-07, 7.25458e-06, 8.22173e-07, -5.14298e-06 +# 8.11523e-07, 7.73772e-07, 9.07225e-07, 8.22173e-07, 7.20964e-06, -4.1653e-06 +# -4.02963e-07, 1.59025e-06, 2.88878e-07, -5.14298e-06, -4.1653e-06, 0.0137105 +-162.715,0.963989,0.212886,2,3,0,163.761,0.999942,0.999552,0.998004,0.999176,0.998855,0.998754 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+-163.732,0.74395,0.212886,2,3,0,167.325,0.998063,0.997614,0.996795,0.997041,0.99752,1.02828 +-163.942,0.778934,0.212886,3,15,0,166.826,0.999297,0.998282,0.998238,0.998535,0.997924,1.15937 +-162.648,0.967649,0.212886,3,7,0,164.779,0.998826,0.998166,0.997465,0.998166,0.99769,0.942077 +-163.636,0.731218,0.212886,3,7,0,164.229,0.999009,0.998286,0.997079,0.997525,0.997845,0.959725 +-165.453,0.593154,0.212886,3,15,0,167.275,0.99993,1.00017,0.999224,1.0007,0.999461,1.06392 +-164.22,1,0.212886,2,3,0,166.015,1.00124,0.999118,0.999307,0.999346,0.999475,1.06511 +-163.706,0.621293,0.212886,2,3,0,167.577,0.999932,0.998876,0.998065,0.999653,0.999417,1.06341 +# +# Elapsed Time: 0.034548 seconds (Warm-up) +# 0.079837 seconds (Sampling) +# 0.114385 seconds (Total) +# diff --git a/examples/sblrc-blr/plot_stepsize.R b/examples/sblrc-blr/plot_stepsize.R new file mode 100644 index 0000000000..35f952d646 --- /dev/null +++ b/examples/sblrc-blr/plot_stepsize.R @@ -0,0 +1,6 @@ +sampler_params <- rstan:::get_sampler_params(stanfit, inc_warmup = TRUE) +stepsizes = data.frame(10:n_warmup+50,sapply(sampler_params, function(x) x[, "stepsize__"])[10:n_warmup+50,]) +colnames(stepsizes) <- c("warmup_iter", "chain1","chain2","chain3","chain4") +stepsize <- melt(stepsizes , id.vars = 'warmup_iter', variable.name = 'dt') +ggplot(stepsize, aes(warmup_iter,value)) + geom_line(aes(colour = dt)) + diff --git a/examples/sblrc-blr/run_model.sh b/examples/sblrc-blr/run_model.sh new file mode 100755 index 0000000000..71f6309e7b --- /dev/null +++ b/examples/sblrc-blr/run_model.sh @@ -0,0 +1,6 @@ +#/bin/bash + +./sblrc-blr sample save_warmup=1 max_num_warmup=1100 algorithm=hmc metric=dense_e adapt delta=0.95 data file=sblrc-blr.data.R output file=$1.output.csv id=$1 random seed=8857113 + +# run in parallel +# seq 4 | parallel -j 4 --workdir $PWD ./run_model.sh {} ::: 0 1 2 3 diff --git a/examples/sblrc-blr/sblrc-blr.data.R b/examples/sblrc-blr/sblrc-blr.data.R new file mode 100644 index 0000000000..55afa241fc --- /dev/null +++ b/examples/sblrc-blr/sblrc-blr.data.R @@ -0,0 +1,32 @@ +y <- c( + 35.5808956, -36.1362447, -87.0417034, 147.2350640, -100.3342924, + 59.9576148, -172.5566200, 54.0821936, -165.5283597, -69.1805985, + -74.0668402, 6.0148602, -199.2239815, 12.6254614, 133.3058632, + 145.2521716, -39.1250068, 4.1120437, 44.6792394, 123.8911295, + -6.6643489, -44.2349653, -210.5159344, -8.1230078, 43.8061525, + -292.4409359, -234.9837398, -42.4561198, 14.2849175, 51.1587507, + -31.8414251, 10.2703842, -34.9912915, -16.7515377, 55.6619281, + -80.0036121, -27.5385821, -55.0547309, -117.6209653, 31.7677377, + 2.8135574, 118.8103386, -67.6146525, -132.0807482, 216.2991095, + -43.3149346, 10.4292821, -132.7868434, 200.4738402, 196.1505445, + 9.1638519, 146.5370546, -103.4940561, -57.6962660, -149.6931941, + 155.9312763, -6.9317089, 263.6352212, -28.2865020, -56.1693906, + -207.1793359, 43.5455222, 59.0530295, -53.7065970, -172.9297544, + -119.5875585, 53.0205877, -63.1153662, 16.0002200, -111.8903002, + -121.7334833, 192.7397090, -136.5879661, -184.9321177, -161.1550120, + 37.6593053, 38.1017857, -101.0563919, -34.0141978, 0.5460303, + -158.5454830, -168.2126831, -140.0568737, -46.5548919, -153.2915774, + -1.7783830, 29.4492144, 235.3524355, -62.9845012, -151.1576573, + -38.5003684, -126.1919007, -62.7806929, 31.4918120, 10.6828779, + 73.8264531, 68.1383013, -226.7417293, -58.9914688, 51.0837533) + +X <- structure(c( 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.Dim = c(100,5)) + +D <- 5 + +N <- 100 diff --git a/examples/sblrc-blr/sblrc-blr.hpp b/examples/sblrc-blr/sblrc-blr.hpp new file mode 100644 index 0000000000..031b76287c --- /dev/null +++ b/examples/sblrc-blr/sblrc-blr.hpp @@ -0,0 +1,484 @@ + +// Code generated by stanc 11a0fa5 +#include +namespace sblrc_blr_model_namespace { + +template +std::vector resize_to_match__(std::vector& dst, const std::vector& src) { + dst.resize(src.size()); + return dst; +} + +template +Eigen::Matrix +resize_to_match__(Eigen::Matrix& dst, const Eigen::Matrix& src) { + dst.resize(src.rows(), src.cols()); + return dst; +} + +template +Eigen::Matrix +resize_to_match__(Eigen::Matrix& dst, const Eigen::Matrix& src) { + dst.resize(src.size()); + return dst; +} + +template +Eigen::Matrix +resize_to_match__(Eigen::Matrix& dst, const Eigen::Matrix& src) { + dst.resize(src.size()); + return dst; +} +std::vector to_doubles__(std::initializer_list x) { + return x; +} + +std::vector to_vars__(std::initializer_list x) { + return x; +} + +inline void validate_positive_index(const char* var_name, const char* expr, + int val) { + if (val < 1) { + std::stringstream msg; + msg << "Found dimension size less than one in simplex declaration" + << "; variable=" << var_name << "; dimension size expression=" << expr + << "; expression value=" << val; + std::string msg_str(msg.str()); + throw std::invalid_argument(msg_str.c_str()); + } +} + +inline void validate_unit_vector_index(const char* var_name, const char* expr, + int val) { + if (val <= 1) { + std::stringstream msg; + if (val == 1) { + msg << "Found dimension size one in unit vector declaration." + << " One-dimensional unit vector is discrete" + << " but the target distribution must be continuous." + << " variable=" << var_name << "; dimension size expression=" << expr; + } else { + msg << "Found dimension size less than one in unit vector declaration" + << "; variable=" << var_name << "; dimension size expression=" << expr + << "; expression value=" << val; + } + std::string msg_str(msg.str()); + throw std::invalid_argument(msg_str.c_str()); + } +} + + +using std::istream; +using std::string; +using std::stringstream; +using std::vector; +using stan::io::dump; +using stan::math::lgamma; +using stan::model::model_base_crtp; +using stan::model::rvalue; +using stan::model::cons_list; +using stan::model::index_uni; +using stan::model::index_max; +using stan::model::index_min; +using stan::model::index_min_max; +using stan::model::index_multi; +using stan::model::index_omni; +using stan::model::nil_index_list; +using namespace stan::math; + +static int current_statement__ = 0; +static const std::vector locations_array__ = {" (found before start of program)", + " (in 'examples/sblrc-blr/sblrc-blr.stan', line 9, column 2 to column 18)", + " (in 'examples/sblrc-blr/sblrc-blr.stan', line 10, column 2 to column 23)", + " (in 'examples/sblrc-blr/sblrc-blr.stan', line 15, column 2 to column 38)", + " (in 'examples/sblrc-blr/sblrc-blr.stan', line 16, column 2 to column 39)", + " (in 'examples/sblrc-blr/sblrc-blr.stan', line 18, column 2 to column 45)", + " (in 'examples/sblrc-blr/sblrc-blr.stan', line 2, column 2 to column 18)", + " (in 'examples/sblrc-blr/sblrc-blr.stan', line 3, column 2 to column 18)", + " (in 'examples/sblrc-blr/sblrc-blr.stan', line 4, column 2 to column 18)", + " (in 'examples/sblrc-blr/sblrc-blr.stan', line 5, column 2 to column 15)"}; + + +class sblrc_blr_model : public model_base_crtp { + + private: + int pos__; + int N; + int D; + Eigen::Matrix X; + Eigen::Matrix y; + + public: + ~sblrc_blr_model() { } + + std::string model_name() const { return "sblrc_blr_model"; } + + sblrc_blr_model(stan::io::var_context& context__, + unsigned int random_seed__ = 0, + std::ostream* pstream__ = nullptr) : model_base_crtp(0) { + typedef double local_scalar_t__; + boost::ecuyer1988 base_rng__ = + stan::services::util::create_rng(random_seed__, 0); + (void) base_rng__; // suppress unused var warning + static const char* function__ = "sblrc_blr_model_namespace::sblrc_blr_model"; + (void) function__; // suppress unused var warning + + try { + + pos__ = 1; + context__.validate_dims("data initialization","N","int", + context__.to_vec()); + + current_statement__ = 6; + N = context__.vals_i("N")[(1 - 1)]; + context__.validate_dims("data initialization","D","int", + context__.to_vec()); + + current_statement__ = 7; + D = context__.vals_i("D")[(1 - 1)]; + current_statement__ = 8; + validate_non_negative_index("X", "N", N); + current_statement__ = 8; + validate_non_negative_index("X", "D", D); + context__.validate_dims("data initialization","X","double", + context__.to_vec(N, D)); + X = Eigen::Matrix(N, D); + + { + std::vector X_flat__; + current_statement__ = 8; + assign(X_flat__, nil_index_list(), context__.vals_r("X"), + "assigning variable X_flat__"); + current_statement__ = 8; + pos__ = 1; + current_statement__ = 8; + for (size_t sym1__ = 1; sym1__ <= D; ++sym1__) { + current_statement__ = 8; + for (size_t sym2__ = 1; sym2__ <= N; ++sym2__) { + current_statement__ = 8; + assign(X, + cons_list(index_uni(sym2__), + cons_list(index_uni(sym1__), nil_index_list())), + X_flat__[(pos__ - 1)], "assigning variable X"); + current_statement__ = 8; + pos__ = (pos__ + 1);}} + } + current_statement__ = 9; + validate_non_negative_index("y", "N", N); + context__.validate_dims("data initialization","y","double", + context__.to_vec(N)); + y = Eigen::Matrix(N); + + { + std::vector y_flat__; + current_statement__ = 9; + assign(y_flat__, nil_index_list(), context__.vals_r("y"), + "assigning variable y_flat__"); + current_statement__ = 9; + pos__ = 1; + current_statement__ = 9; + for (size_t sym1__ = 1; sym1__ <= N; ++sym1__) { + current_statement__ = 9; + assign(y, cons_list(index_uni(sym1__), nil_index_list()), + y_flat__[(pos__ - 1)], "assigning variable y"); + current_statement__ = 9; + pos__ = (pos__ + 1);} + } + current_statement__ = 6; + current_statement__ = 6; + check_greater_or_equal(function__, "N", N, 0); + current_statement__ = 7; + current_statement__ = 7; + check_greater_or_equal(function__, "D", D, 0); + } catch (const std::exception& e) { + stan::lang::rethrow_located(e, locations_array__[current_statement__]); + // Next line prevents compiler griping about no return + throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ***"); + } + num_params_r__ = 0U; + + try { + current_statement__ = 1; + validate_non_negative_index("beta", "D", D); + num_params_r__ += D; + num_params_r__ += 1; + } catch (const std::exception& e) { + stan::lang::rethrow_located(e, locations_array__[current_statement__]); + // Next line prevents compiler griping about no return + throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ***"); + } + } + template + T__ log_prob(std::vector& params_r__, std::vector& params_i__, + std::ostream* pstream__ = 0) const { + typedef T__ local_scalar_t__; + T__ lp__(0.0); + stan::math::accumulator lp_accum__; + static const char* function__ = "sblrc_blr_model_namespace::log_prob"; +(void) function__; // suppress unused var warning + + stan::io::reader in__(params_r__, params_i__); + + try { + current_statement__ = 1; + validate_non_negative_index("beta", "D", D); + Eigen::Matrix beta; + beta = Eigen::Matrix(D); + + current_statement__ = 1; + beta = in__.vector(D); + local_scalar_t__ sigma; + + current_statement__ = 2; + sigma = in__.scalar(); + current_statement__ = 2; + if (jacobian__) { + current_statement__ = 2; + sigma = stan::math::lb_constrain(sigma, 0, lp__); + } else { + current_statement__ = 2; + sigma = stan::math::lb_constrain(sigma, 0); + } + { + current_statement__ = 3; + lp_accum__.add(normal_lpdf(beta, 0, 10)); + current_statement__ = 4; + lp_accum__.add(normal_lpdf(sigma, 0, 10)); + current_statement__ = 5; + lp_accum__.add(normal_lpdf(y, multiply(X, beta), sigma)); + } + } catch (const std::exception& e) { + stan::lang::rethrow_located(e, locations_array__[current_statement__]); + // Next line prevents compiler griping about no return + throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ***"); + } + lp_accum__.add(lp__); + return lp_accum__.sum(); + } // log_prob() + + template + void write_array(RNG& base_rng__, std::vector& params_r__, + std::vector& params_i__, std::vector& vars__, + bool emit_transformed_parameters__ = true, + bool emit_generated_quantities__ = true, + std::ostream* pstream__ = 0) const { + typedef double local_scalar_t__; + vars__.resize(0); + stan::io::reader in__(params_r__, params_i__); + static const char* function__ = "sblrc_blr_model_namespace::write_array"; +(void) function__; // suppress unused var warning + + (void) function__; // suppress unused var warning + + double lp__ = 0.0; + (void) lp__; // dummy to suppress unused var warning + stan::math::accumulator lp_accum__; + + try { + current_statement__ = 1; + validate_non_negative_index("beta", "D", D); + Eigen::Matrix beta; + beta = Eigen::Matrix(D); + + current_statement__ = 1; + beta = in__.vector(D); + double sigma; + + current_statement__ = 2; + sigma = in__.scalar(); + current_statement__ = 2; + sigma = stan::math::lb_constrain(sigma, 0); + for (size_t sym1__ = 1; sym1__ <= D; ++sym1__) { + vars__.push_back(beta[(sym1__ - 1)]);} + vars__.push_back(sigma); + if (logical_negation((primitive_value(emit_transformed_parameters__) || + primitive_value(emit_generated_quantities__)))) { + return ; + } + if (logical_negation(emit_generated_quantities__)) { + return ; + } + } catch (const std::exception& e) { + stan::lang::rethrow_located(e, locations_array__[current_statement__]); + // Next line prevents compiler griping about no return + throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ***"); + } + } // write_array() + + void transform_inits(const stan::io::var_context& context__, + std::vector& params_i__, + std::vector& vars__, std::ostream* pstream__) const { + typedef double local_scalar_t__; + vars__.resize(0); + vars__.reserve(num_params_r__); + + try { + int pos__; + + pos__ = 1; + current_statement__ = 1; + validate_non_negative_index("beta", "D", D); + Eigen::Matrix beta; + beta = Eigen::Matrix(D); + + { + std::vector beta_flat__; + current_statement__ = 1; + assign(beta_flat__, nil_index_list(), context__.vals_r("beta"), + "assigning variable beta_flat__"); + current_statement__ = 1; + pos__ = 1; + current_statement__ = 1; + for (size_t sym1__ = 1; sym1__ <= D; ++sym1__) { + current_statement__ = 1; + assign(beta, cons_list(index_uni(sym1__), nil_index_list()), + beta_flat__[(pos__ - 1)], "assigning variable beta"); + current_statement__ = 1; + pos__ = (pos__ + 1);} + } + double sigma; + + current_statement__ = 2; + sigma = context__.vals_r("sigma")[(1 - 1)]; + current_statement__ = 2; + sigma = stan::math::lb_free(sigma, 0); + for (size_t sym1__ = 1; sym1__ <= D; ++sym1__) { + vars__.push_back(beta[(sym1__ - 1)]);} + vars__.push_back(sigma); + } catch (const std::exception& e) { + stan::lang::rethrow_located(e, locations_array__[current_statement__]); + // Next line prevents compiler griping about no return + throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ***"); + } + } // transform_inits() + + void get_param_names(std::vector& names__) const { + + names__.resize(0); + names__.push_back("beta"); + names__.push_back("sigma"); + } // get_param_names() + + void get_dims(std::vector>& dimss__) const { + dimss__.resize(0); + std::vector dims__; + dims__.push_back(D); + dimss__.push_back(dims__); + dims__.resize(0); + dimss__.push_back(dims__); + dims__.resize(0); + + } // get_dims() + + void constrained_param_names(std::vector& param_names__, + bool emit_transformed_parameters__ = true, + bool emit_generated_quantities__ = true) const { + + for (size_t sym1__ = 1; sym1__ <= D; ++sym1__) { + { + param_names__.push_back(std::string() + "beta" + '.' + std::to_string(sym1__)); + }} + param_names__.push_back(std::string() + "sigma"); + if (emit_transformed_parameters__) { + + } + + if (emit_generated_quantities__) { + + } + + } // constrained_param_names() + + void unconstrained_param_names(std::vector& param_names__, + bool emit_transformed_parameters__ = true, + bool emit_generated_quantities__ = true) const { + + for (size_t sym1__ = 1; sym1__ <= D; ++sym1__) { + { + param_names__.push_back(std::string() + "beta" + '.' + std::to_string(sym1__)); + }} + param_names__.push_back(std::string() + "sigma"); + if (emit_transformed_parameters__) { + + } + + if (emit_generated_quantities__) { + + } + + } // unconstrained_param_names() + + std::string get_constrained_sizedtypes() const { + stringstream s__; + s__ << "[{\"name\":\"beta\",\"type\":{\"name\":\"vector\",\"length\":" << D << "},\"block\":\"parameters\"},{\"name\":\"sigma\",\"type\":{\"name\":\"real\"},\"block\":\"parameters\"}]"; + return s__.str(); + } // get_constrained_sizedtypes() + + std::string get_unconstrained_sizedtypes() const { + stringstream s__; + s__ << "[{\"name\":\"beta\",\"type\":{\"name\":\"vector\",\"length\":" << D << "},\"block\":\"parameters\"},{\"name\":\"sigma\",\"type\":{\"name\":\"real\"},\"block\":\"parameters\"}]"; + return s__.str(); + } // get_unconstrained_sizedtypes() + + + // Begin method overload boilerplate + template + void write_array(RNG& base_rng__, + Eigen::Matrix& params_r, + Eigen::Matrix& vars, + bool emit_transformed_parameters__ = true, + bool emit_generated_quantities__ = true, + std::ostream* pstream = 0) const { + std::vector params_r_vec(params_r.size()); + for (int i = 0; i < params_r.size(); ++i) + params_r_vec[i] = params_r(i); + std::vector vars_vec; + std::vector params_i_vec; + write_array(base_rng__, params_r_vec, params_i_vec, vars_vec, + emit_transformed_parameters__, emit_generated_quantities__, pstream); + vars.resize(vars_vec.size()); + for (int i = 0; i < vars.size(); ++i) + vars(i) = vars_vec[i]; + } + + template + T_ log_prob(Eigen::Matrix& params_r, + std::ostream* pstream = 0) const { + std::vector vec_params_r; + vec_params_r.reserve(params_r.size()); + for (int i = 0; i < params_r.size(); ++i) + vec_params_r.push_back(params_r(i)); + std::vector vec_params_i; + return log_prob(vec_params_r, vec_params_i, pstream); + } + + void transform_inits(const stan::io::var_context& context, + Eigen::Matrix& params_r, + std::ostream* pstream__) const { + std::vector params_r_vec; + std::vector params_i_vec; + transform_inits(context, params_i_vec, params_r_vec, pstream__); + params_r.resize(params_r_vec.size()); + for (int i = 0; i < params_r.size(); ++i) + params_r(i) = params_r_vec[i]; + } + +}; +} +typedef sblrc_blr_model_namespace::sblrc_blr_model stan_model; + +#ifndef USING_R + +// Boilerplate +stan::model::model_base& new_model( + stan::io::var_context& data_context, + unsigned int seed, + std::ostream* msg_stream) { + stan_model* m = new stan_model(data_context, seed, msg_stream); + return *m; +} + +#endif + + diff --git a/examples/sblrc-blr/sblrc-blr.stan b/examples/sblrc-blr/sblrc-blr.stan new file mode 100644 index 0000000000..8fe9b63dc6 --- /dev/null +++ b/examples/sblrc-blr/sblrc-blr.stan @@ -0,0 +1,19 @@ +data { + int N; + int D; + matrix [N, D] X; + vector [N] y; +} + +parameters { + vector [D] beta; + real sigma; +} + +model { + // prior + target += normal_lpdf(beta | 0, 10); + target += normal_lpdf(sigma | 0, 10); + // likelihood + target += normal_lpdf(y | X * beta, sigma); +} diff --git a/examples/sir/0.output.csv b/examples/sir/0.output.csv new file mode 100644 index 0000000000..4f814510b0 --- /dev/null +++ b/examples/sir/0.output.csv @@ -0,0 +1,2056 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = sir_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 0 (Default) +# data +# file = sir.data.R +# init = 2 (Default) +# random +# seed = 5069125 +# output +# file = 0.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) 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stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = sir_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 1 +# data +# file = sir.data.R +# init = 2 (Default) +# random +# seed = 5069125 +# output +# file = 1.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,beta,gamma,xi,delta,y.1.1,y.2.1,y.3.1,y.4.1,y.5.1,y.6.1,y.7.1,y.8.1,y.9.1,y.10.1,y.11.1,y.12.1,y.13.1,y.14.1,y.15.1,y.16.1,y.17.1,y.18.1,y.19.1,y.20.1,y.1.2,y.2.2,y.3.2,y.4.2,y.5.2,y.6.2,y.7.2,y.8.2,y.9.2,y.10.2,y.11.2,y.12.2,y.13.2,y.14.2,y.15.2,y.16.2,y.17.2,y.18.2,y.19.2,y.20.2,y.1.3,y.2.3,y.3.3,y.4.3,y.5.3,y.6.3,y.7.3,y.8.3,y.9.3,y.10.3,y.11.3,y.12.3,y.13.3,y.14.3,y.15.3,y.16.3,y.17.3,y.18.3,y.19.3,y.20.3,y.1.4,y.2.4,y.3.4,y.4.4,y.5.4,y.6.4,y.7.4,y.8.4,y.9.4,y.10.4,y.11.4,y.12.4,y.13.4,y.14.4,y.15.4,y.16.4,y.17.4,y.18.4,y.19.4,y.20.4 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stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = sir_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 2 +# data +# file = sir.data.R +# init = 2 (Default) +# random +# seed = 5069125 +# output +# file = 2.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,beta,gamma,xi,delta,y.1.1,y.2.1,y.3.1,y.4.1,y.5.1,y.6.1,y.7.1,y.8.1,y.9.1,y.10.1,y.11.1,y.12.1,y.13.1,y.14.1,y.15.1,y.16.1,y.17.1,y.18.1,y.19.1,y.20.1,y.1.2,y.2.2,y.3.2,y.4.2,y.5.2,y.6.2,y.7.2,y.8.2,y.9.2,y.10.2,y.11.2,y.12.2,y.13.2,y.14.2,y.15.2,y.16.2,y.17.2,y.18.2,y.19.2,y.20.2,y.1.3,y.2.3,y.3.3,y.4.3,y.5.3,y.6.3,y.7.3,y.8.3,y.9.3,y.10.3,y.11.3,y.12.3,y.13.3,y.14.3,y.15.3,y.16.3,y.17.3,y.18.3,y.19.3,y.20.3,y.1.4,y.2.4,y.3.4,y.4.4,y.5.4,y.6.4,y.7.4,y.8.4,y.9.4,y.10.4,y.11.4,y.12.4,y.13.4,y.14.4,y.15.4,y.16.4,y.17.4,y.18.4,y.19.4,y.20.4 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+30683.8,0.830309,0.566141,2,7,0,-30676.9,0.999095,0.199206,11.2587,0.374129,9592.71,9158.97,8594.71,7918.1,7182.5,6461.11,5819.35,5293.96,4890.85,4595.83,4386.88,4242.14,4143.34,4076.56,4031.7,4001.71,3981.7,3968.38,3959.52,3953.64,207.978,293.238,384.791,465.789,513.545,513.206,466.987,391.593,307.382,229.434,165.075,115.722,79.6768,54.1888,36.5492,24.5145,16.3812,10.9191,7.26618,4.83001,199.309,547.791,1020.5,1616.11,2303.95,3025.68,3713.66,4314.45,4801.77,5174.74,5448.04,5642.14,5776.98,5869.25,5931.75,5973.78,6001.92,6020.7,6033.21,6041.53,5596.97,7849.21,10534.2,13126.3,14972.6,15517.8,14631.6,12666.7,10209.9,7780.48,5685.32,4030.28,2796.75,1912.4,1294.63,870.501,582.661,388.813,258.931,172.203 +30683.7,1,0.566141,2,3,0,-30682.9,1.02148,0.19698,11.1424,0.388214,9594.28,9171.03,8625.67,7975.71,7270.1,6575.72,5953.21,5438.14,5038.14,4741.72,4529.19,4380.2,4277.35,4207.06,4159.34,4127.1,4105.38,4090.78,4080.98,4074.4,207.581,289.175,375.933,452.423,498.116,499.409,457.745,387.743,307.949,232.715,169.521,120.281,83.785,57.6243,39.2885,26.6293,17.977,12.1034,8.13417,5.45997,198.138,539.8,998.394,1571.87,2231.78,2924.87,3589.05,4174.12,4653.91,5025.56,5301.29,5499.51,5638.87,5735.32,5801.37,5846.27,5876.64,5897.12,5910.89,5920.14,5371.43,7441,9879.76,12214,13876.1,14386.5,13625.8,11887.6,9677.41,7457.16,5512.56,3953.42,2774.84,1918.56,1312.85,892.046,603.222,406.595,273.463,183.653 +# +# Elapsed Time: 10.4531 seconds (Warm-up) +# 3.1745 seconds (Sampling) +# 13.6276 seconds (Total) +# diff --git a/examples/sir/3.output.csv b/examples/sir/3.output.csv new file mode 100644 index 0000000000..5ac3f5de97 --- /dev/null +++ b/examples/sir/3.output.csv @@ -0,0 +1,2056 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = sir_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 1 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 3 +# data +# file = sir.data.R +# init = 2 (Default) +# random +# seed = 5069125 +# output +# file = 3.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,beta,gamma,xi,delta,y.1.1,y.2.1,y.3.1,y.4.1,y.5.1,y.6.1,y.7.1,y.8.1,y.9.1,y.10.1,y.11.1,y.12.1,y.13.1,y.14.1,y.15.1,y.16.1,y.17.1,y.18.1,y.19.1,y.20.1,y.1.2,y.2.2,y.3.2,y.4.2,y.5.2,y.6.2,y.7.2,y.8.2,y.9.2,y.10.2,y.11.2,y.12.2,y.13.2,y.14.2,y.15.2,y.16.2,y.17.2,y.18.2,y.19.2,y.20.2,y.1.3,y.2.3,y.3.3,y.4.3,y.5.3,y.6.3,y.7.3,y.8.3,y.9.3,y.10.3,y.11.3,y.12.3,y.13.3,y.14.3,y.15.3,y.16.3,y.17.3,y.18.3,y.19.3,y.20.3,y.1.4,y.2.4,y.3.4,y.4.4,y.5.4,y.6.4,y.7.4,y.8.4,y.9.4,y.10.4,y.11.4,y.12.4,y.13.4,y.14.4,y.15.4,y.16.4,y.17.4,y.18.4,y.19.4,y.20.4 +26369.1,1,0.00390625,3,7,0,17366.1,3.62823,5.35592,4.51241,0.0525888,7943.92,6572.58,5648.92,5017.2,4578.14,4268.51,4047.44,3888.02,3772.15,3687.41,3625.14,3579.23,3545.28,3520.13,3501.46,3487.59,3477.28,3469.61,3463.9,3459.65,44.9301,30.073,20.4044,14.0705,9.85456,6.99554,5.02152,3.63669,2.65212,1.9445,1.43153,1.05717,0.782539,0.580278,0.430866,0.320245,0.238202,0.177275,0.131986,0.0982996,2011.15,3397.35,4330.67,4968.73,5412,5724.49,5947.54,6108.34,6225.2,6310.65,6373.43,6419.72,6453.94,6479.29,6498.11,6512.08,6522.48,6530.21,6535.96,6540.25,8327.53,6728.01,5306.07,4116.61,3157.87,2403.31,1818.79,1370.89,1030.27,772.64,578.527,432.684,323.332,241.464,180.242,134.495,100.334,74.835,55.8085,41.615 +26369.1,0,14.3855,0,1,1,-26368.3,3.62823,5.35592,4.51241,0.0525888,7943.92,6572.58,5648.92,5017.2,4578.14,4268.51,4047.44,3888.02,3772.15,3687.41,3625.14,3579.23,3545.28,3520.13,3501.46,3487.59,3477.28,3469.61,3463.9,3459.65,44.9301,30.073,20.4044,14.0705,9.85456,6.99554,5.02152,3.63669,2.65212,1.9445,1.43153,1.05717,0.782539,0.580278,0.430866,0.320245,0.238202,0.177275,0.131986,0.0982996,2011.15,3397.35,4330.67,4968.73,5412,5724.49,5947.54,6108.34,6225.2,6310.65,6373.43,6419.72,6453.94,6479.29,6498.11,6512.08,6522.48,6530.21,6535.96,6540.25,8327.53,6728.01,5306.07,4116.61,3157.87,2403.31,1818.79,1370.89,1030.27,772.64,578.527,432.684,323.332,241.464,180.242,134.495,100.334,74.835,55.8085,41.615 +26369.1,0,2.43117,0,1,1,-26365.6,3.62823,5.35592,4.51241,0.0525888,7943.92,6572.58,5648.92,5017.2,4578.14,4268.51,4047.44,3888.02,3772.15,3687.41,3625.14,3579.23,3545.28,3520.13,3501.46,3487.59,3477.28,3469.61,3463.9,3459.65,44.9301,30.073,20.4044,14.0705,9.85456,6.99554,5.02152,3.63669,2.65212,1.9445,1.43153,1.05717,0.782539,0.580278,0.430866,0.320245,0.238202,0.177275,0.131986,0.0982996,2011.15,3397.35,4330.67,4968.73,5412,5724.49,5947.54,6108.34,6225.2,6310.65,6373.43,6419.72,6453.94,6479.29,6498.11,6512.08,6522.48,6530.21,6535.96,6540.25,8327.53,6728.01,5306.07,4116.61,3157.87,2403.31,1818.79,1370.89,1030.27,772.64,578.527,432.684,323.332,241.464,180.242,134.495,100.334,74.835,55.8085,41.615 +26369.1,0,0.239791,0,1,1,-26368.8,3.62823,5.35592,4.51241,0.0525888,7943.92,6572.58,5648.92,5017.2,4578.14,4268.51,4047.44,3888.02,3772.15,3687.41,3625.14,3579.23,3545.28,3520.13,3501.46,3487.59,3477.28,3469.61,3463.9,3459.65,44.9301,30.073,20.4044,14.0705,9.85456,6.99554,5.02152,3.63669,2.65212,1.9445,1.43153,1.05717,0.782539,0.580278,0.430866,0.320245,0.238202,0.177275,0.131986,0.0982996,2011.15,3397.35,4330.67,4968.73,5412,5724.49,5947.54,6108.34,6225.2,6310.65,6373.43,6419.72,6453.94,6479.29,6498.11,6512.08,6522.48,6530.21,6535.96,6540.25,8327.53,6728.01,5306.07,4116.61,3157.87,2403.31,1818.79,1370.89,1030.27,772.64,578.527,432.684,323.332,241.464,180.242,134.495,100.334,74.835,55.8085,41.615 +26369.1,0,0.0186273,0,1,1,-26368.1,3.62823,5.35592,4.51241,0.0525888,7943.92,6572.58,5648.92,5017.2,4578.14,4268.51,4047.44,3888.02,3772.15,3687.41,3625.14,3579.23,3545.28,3520.13,3501.46,3487.59,3477.28,3469.61,3463.9,3459.65,44.9301,30.073,20.4044,14.0705,9.85456,6.99554,5.02152,3.63669,2.65212,1.9445,1.43153,1.05717,0.782539,0.580278,0.430866,0.320245,0.238202,0.177275,0.131986,0.0982996,2011.15,3397.35,4330.67,4968.73,5412,5724.49,5947.54,6108.34,6225.2,6310.65,6373.43,6419.72,6453.94,6479.29,6498.11,6512.08,6522.48,6530.21,6535.96,6540.25,8327.53,6728.01,5306.07,4116.61,3157.87,2403.31,1818.79,1370.89,1030.27,772.64,578.527,432.684,323.332,241.464,180.242,134.495,100.334,74.835,55.8085,41.615 +26646.7,1,0.00130482,2,3,0,-26368.3,3.61334,5.30353,4.516,0.0509818,7940.58,6552.37,5609.5,4960.14,4505.99,4183.79,3952.34,3784.39,3661.51,3571.03,3504.07,3454.33,3417.26,3389.59,3368.89,3353.38,3341.76,3333.04,3326.49,3321.57,45.7177,30.8864,21.1141,14.6547,10.3261,7.37433,5.32604,3.882,2.85005,2.1043,1.5605,1.16111,0.866162,0.647394,0.484596,0.363141,0.272357,0.204397,0.15347,0.115273,2013.71,3416.75,4369.38,5025.21,5483.68,5808.84,6042.33,6211.73,6335.64,6426.87,6494.37,6544.51,6581.87,6609.76,6630.63,6646.25,6657.97,6666.76,6673.36,6678.31,8431.09,6893.72,5499.21,4313.28,3343.63,2570.62,1964.68,1495.19,1134.35,858.634,648.84,489.693,369.239,278.22,209.53,157.737,118.712,89.3229,67.1984,50.5477 +27078,1,0.00189104,2,3,0,-26653.4,3.54753,5.22055,4.59528,0.0485382,7956.63,6551.83,5582.66,4906.55,4428.39,4085.6,3836.86,3654.49,3519.65,3419.28,3344.15,3287.68,3245.09,3212.9,3188.51,3170,3155.95,3145.27,3137.14,3130.95,46.5866,32.0272,22.2025,15.5934,11.1051,8.01179,5.84545,4.30498,3.19465,2.3851,1.78922,1.34722,1.01735,0.769967,0.583745,0.443148,0.336757,0.256106,0.194886,0.148369,1996.78,3416.14,4395.14,5077.85,5560.51,5906.39,6157.3,6341.2,6477.15,6578.34,6654.06,6710.98,6753.89,6786.33,6810.91,6829.55,6843.71,6854.48,6862.67,6868.9,8601.05,7171.47,5828.7,4654.09,3670.17,2868.68,2227.9,1722.18,1326.69,1019.41,781.81,598.732,458.031,350.11,267.453,204.215,155.874,118.944,90.7449,69.2205 +27779.6,1,0.00305706,2,3,0,-27103.2,3.39241,5.03331,4.72116,0.0437358,8004.66,6577.72,5561.59,4834.17,4308.24,3923.63,3639.2,3426.7,3266.54,3144.93,3052.02,2980.68,2925.69,2883.16,2850.18,2824.56,2804.62,2789.08,2776.96,2767.5,48.2114,34.3341,24.4867,17.6083,12.8025,9.41588,7.00006,5.2538,3.97526,3.02825,2.31963,1.78482,1.37827,1.06739,0.828522,0.644277,0.501719,0.391147,0.305213,0.238326,1947.13,3387.94,4413.92,5148.22,5678.95,6066.95,6353.8,6568.04,6729.48,6852.04,6945.66,7017.53,7072.93,7115.78,7148.99,7174.8,7194.88,7210.53,7222.73,7232.26,8929.89,7729,6512.55,5383.38,4389.01,3542.58,2838.34,2261.65,1794.72,1419.75,1120.46,882.651,694.343,545.619,428.392,336.133,263.609,206.652,161.952,126.89 +29110.2,1,0.00530085,3,7,0,-27826.8,2.47735,4.4898,5.30451,0.0308923,8447.7,7187.07,6179.97,5382.38,4752.61,4254.89,3860.23,3545.82,3293.99,3091.19,2926.99,2793.39,2684.18,2594.55,2520.72,2459.72,2409.17,2367.18,2332.24,2303.1,44.8791,36.1069,28.691,22.6712,17.8999,14.1651,11.256,8.9902,7.21981,5.82968,4.73163,3.85881,3.16064,2.59879,2.14409,1.7742,1.47191,1.22384,1.01952,0.8507,1507.43,2776.82,3791.34,4594.95,5229.49,5730.94,6128.51,6445.19,6698.79,6902.98,7068.28,7202.75,7312.66,7402.85,7477.13,7538.51,7589.36,7631.59,7666.74,7696.05,9656.73,9122.24,8421.72,7634.18,6820.92,6025.02,5274.03,4583.52,3960.57,3406.49,2919.02,2493.72,2125.14,1807.36,1534.54,1301.12,1101.95,932.381,788.29,666.031 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+1,1406 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = sir_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 0 (Default) +# data +# file = sir.data.R +# init = 2 (Default) +# random +# seed = 5069125 +# output +# file = mpi.0.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,beta,gamma,xi,delta,y.1.1,y.2.1,y.3.1,y.4.1,y.5.1,y.6.1,y.7.1,y.8.1,y.9.1,y.10.1,y.11.1,y.12.1,y.13.1,y.14.1,y.15.1,y.16.1,y.17.1,y.18.1,y.19.1,y.20.1,y.1.2,y.2.2,y.3.2,y.4.2,y.5.2,y.6.2,y.7.2,y.8.2,y.9.2,y.10.2,y.11.2,y.12.2,y.13.2,y.14.2,y.15.2,y.16.2,y.17.2,y.18.2,y.19.2,y.20.2,y.1.3,y.2.3,y.3.3,y.4.3,y.5.3,y.6.3,y.7.3,y.8.3,y.9.3,y.10.3,y.11.3,y.12.3,y.13.3,y.14.3,y.15.3,y.16.3,y.17.3,y.18.3,y.19.3,y.20.3,y.1.4,y.2.4,y.3.4,y.4.4,y.5.4,y.6.4,y.7.4,y.8.4,y.9.4,y.10.4,y.11.4,y.12.4,y.13.4,y.14.4,y.15.4,y.16.4,y.17.4,y.18.4,y.19.4,y.20.4 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+1,1406 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = sir_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 1 +# data +# file = sir.data.R +# init = 2 (Default) +# random +# seed = 5069125 +# output +# file = mpi.1.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,beta,gamma,xi,delta,y.1.1,y.2.1,y.3.1,y.4.1,y.5.1,y.6.1,y.7.1,y.8.1,y.9.1,y.10.1,y.11.1,y.12.1,y.13.1,y.14.1,y.15.1,y.16.1,y.17.1,y.18.1,y.19.1,y.20.1,y.1.2,y.2.2,y.3.2,y.4.2,y.5.2,y.6.2,y.7.2,y.8.2,y.9.2,y.10.2,y.11.2,y.12.2,y.13.2,y.14.2,y.15.2,y.16.2,y.17.2,y.18.2,y.19.2,y.20.2,y.1.3,y.2.3,y.3.3,y.4.3,y.5.3,y.6.3,y.7.3,y.8.3,y.9.3,y.10.3,y.11.3,y.12.3,y.13.3,y.14.3,y.15.3,y.16.3,y.17.3,y.18.3,y.19.3,y.20.3,y.1.4,y.2.4,y.3.4,y.4.4,y.5.4,y.6.4,y.7.4,y.8.4,y.9.4,y.10.4,y.11.4,y.12.4,y.13.4,y.14.4,y.15.4,y.16.4,y.17.4,y.18.4,y.19.4,y.20.4 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+30683.7,0.939424,0.404453,3,7,0,-30680.5,1.07647,0.187399,9.71614,0.366961,9565.95,9116.9,8539.95,7855.21,7116.47,6395.15,5754,5227.94,4822.48,4523.91,4310.92,4162.22,4059.88,3990.12,3942.87,3910.99,3889.55,3875.16,3865.5,3859.03,228.46,319.084,414.656,498.113,546.678,545.808,497.952,419.869,332.073,250.044,181.596,128.527,89.3423,61.3378,41.7562,28.2631,19.0562,12.8151,8.60293,5.76848,205.595,564.016,1045.39,1646.67,2336.85,3059.04,3748.05,4352.19,4845.45,5226.05,5507.49,5709.25,5850.77,5948.54,6015.37,6060.74,6091.39,6112.03,6125.9,6135.2,5438.98,7526.02,10002.1,12365.2,14033,14520.8,13718.3,11935.6,9690.64,7449.18,5494.78,3933.23,2756.08,1902.76,1300.3,882.423,596.023,401.297,269.612,180.879 +# num_warmup = 350 +# Adaptation terminated +# Step size = 0.504349 +# Elements of inverse mass matrix: +# 0.00171984, -0.00162747, -0.00157795, 0.00158827 +# -0.00162747, 0.00183345, 0.00128871, -0.00193084 +# -0.00157795, 0.00128871, 0.00425703, 0.00162194 +# 0.00158827, -0.00193084, 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+1,1406 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = sir_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 2 +# data +# file = sir.data.R +# init = 2 (Default) +# random +# seed = 5069125 +# output +# file = mpi.2.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,beta,gamma,xi,delta,y.1.1,y.2.1,y.3.1,y.4.1,y.5.1,y.6.1,y.7.1,y.8.1,y.9.1,y.10.1,y.11.1,y.12.1,y.13.1,y.14.1,y.15.1,y.16.1,y.17.1,y.18.1,y.19.1,y.20.1,y.1.2,y.2.2,y.3.2,y.4.2,y.5.2,y.6.2,y.7.2,y.8.2,y.9.2,y.10.2,y.11.2,y.12.2,y.13.2,y.14.2,y.15.2,y.16.2,y.17.2,y.18.2,y.19.2,y.20.2,y.1.3,y.2.3,y.3.3,y.4.3,y.5.3,y.6.3,y.7.3,y.8.3,y.9.3,y.10.3,y.11.3,y.12.3,y.13.3,y.14.3,y.15.3,y.16.3,y.17.3,y.18.3,y.19.3,y.20.3,y.1.4,y.2.4,y.3.4,y.4.4,y.5.4,y.6.4,y.7.4,y.8.4,y.9.4,y.10.4,y.11.4,y.12.4,y.13.4,y.14.4,y.15.4,y.16.4,y.17.4,y.18.4,y.19.4,y.20.4 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+30684.8,0.497504,0.971359,1,3,0,-30683.7,1.00866,0.199311,11.1883,0.379029,9593,9164.73,8611.81,7952.36,7237.04,6534.76,5907.41,5390.59,4991.09,4696.4,4486.06,4339.24,4238.3,4169.59,4123.13,4091.85,4070.85,4056.79,4047.38,4041.09,207.333,289.707,377.279,454.212,499.487,499.421,455.957,384.417,303.773,228.401,165.564,116.926,81.0878,55.5352,37.7122,25.4621,17.1247,11.4873,7.69236,5.14509,199.665,545.562,1010.91,1593.43,2263.48,2965.82,3636.63,4224.99,4705.14,5075.2,5348.38,5543.83,5680.61,5774.88,5839.16,5882.69,5912.02,5931.72,5944.93,5953.77,5498.19,7640.18,10169.4,12589.7,14303.6,14809.1,13988.8,12160.4,9858.17,7562.77,5565.59,3973.9,2777.34,1912.4,1303.45,882.259,594.374,399.165,267.5,179.011 +30684.8,0.735183,0.971359,2,7,0,-30682.7,1.00866,0.199311,11.1883,0.379029,9593,9164.73,8611.81,7952.36,7237.04,6534.76,5907.41,5390.59,4991.09,4696.4,4486.06,4339.24,4238.3,4169.59,4123.13,4091.85,4070.85,4056.79,4047.38,4041.09,207.333,289.707,377.279,454.212,499.487,499.421,455.957,384.417,303.773,228.401,165.564,116.926,81.0878,55.5352,37.7122,25.4621,17.1247,11.4873,7.69236,5.14509,199.665,545.562,1010.91,1593.43,2263.48,2965.82,3636.63,4224.99,4705.14,5075.2,5348.38,5543.83,5680.61,5774.88,5839.16,5882.69,5912.02,5931.72,5944.93,5953.77,5498.19,7640.18,10169.4,12589.7,14303.6,14809.1,13988.8,12160.4,9858.17,7562.77,5565.59,3973.9,2777.34,1912.4,1303.45,882.259,594.374,399.165,267.5,179.011 +# +# Elapsed Time: 22.6148 seconds (Warm-up) +# 2.52552 seconds (Sampling) +# 25.1403 seconds (Total) +# diff --git a/examples/sir/mpi.3.output.csv b/examples/sir/mpi.3.output.csv new file mode 100644 index 0000000000..e666b2d0d6 --- /dev/null +++ b/examples/sir/mpi.3.output.csv @@ -0,0 +1,1406 @@ +# stan_version_major = 2 +# stan_version_minor = 21 +# stan_version_patch = 0 +# model = sir_model +# method = sample (Default) +# sample +# num_samples = 1000 (Default) +# max_num_warmup = 1000 (Default) +# save_warmup = 1 +# thin = 1 (Default) +# adapt +# engaged = 1 (Default) +# gamma = 0.050000000000000003 (Default) +# delta = 0.80000000000000004 (Default) +# kappa = 0.75 (Default) +# t0 = 10 (Default) +# init_buffer = 75 (Default) +# term_buffer = 50 (Default) +# window = 25 (Default) +# num_cross_chains = 4 (Default) +# cross_chain_window = 100 (Default) +# cross_chain_rhat = 1.05 (Default) +# cross_chain_ess = 200 (Default) +# algorithm = hmc (Default) +# hmc +# engine = nuts (Default) +# nuts +# max_depth = 10 (Default) +# metric = dense_e +# metric_file = (Default) +# stepsize = 1 (Default) +# stepsize_jitter = 0 (Default) +# id = 3 +# data +# file = sir.data.R +# init = 2 (Default) +# random +# seed = 5069125 +# output +# file = mpi.3.output.csv +# diagnostic_file = (Default) +# refresh = 100 (Default) +lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,beta,gamma,xi,delta,y.1.1,y.2.1,y.3.1,y.4.1,y.5.1,y.6.1,y.7.1,y.8.1,y.9.1,y.10.1,y.11.1,y.12.1,y.13.1,y.14.1,y.15.1,y.16.1,y.17.1,y.18.1,y.19.1,y.20.1,y.1.2,y.2.2,y.3.2,y.4.2,y.5.2,y.6.2,y.7.2,y.8.2,y.9.2,y.10.2,y.11.2,y.12.2,y.13.2,y.14.2,y.15.2,y.16.2,y.17.2,y.18.2,y.19.2,y.20.2,y.1.3,y.2.3,y.3.3,y.4.3,y.5.3,y.6.3,y.7.3,y.8.3,y.9.3,y.10.3,y.11.3,y.12.3,y.13.3,y.14.3,y.15.3,y.16.3,y.17.3,y.18.3,y.19.3,y.20.3,y.1.4,y.2.4,y.3.4,y.4.4,y.5.4,y.6.4,y.7.4,y.8.4,y.9.4,y.10.4,y.11.4,y.12.4,y.13.4,y.14.4,y.15.4,y.16.4,y.17.4,y.18.4,y.19.4,y.20.4 +26369.1,1,0.00390625,3,7,0,17366.1,3.62823,5.35592,4.51241,0.0525888,7943.92,6572.58,5648.92,5017.2,4578.14,4268.51,4047.44,3888.02,3772.15,3687.41,3625.14,3579.23,3545.28,3520.13,3501.46,3487.59,3477.28,3469.61,3463.9,3459.65,44.9301,30.073,20.4044,14.0705,9.85456,6.99554,5.02152,3.63669,2.65212,1.9445,1.43153,1.05717,0.782539,0.580278,0.430866,0.320245,0.238202,0.177275,0.131986,0.0982996,2011.15,3397.35,4330.67,4968.73,5412,5724.49,5947.54,6108.34,6225.2,6310.65,6373.43,6419.72,6453.94,6479.29,6498.11,6512.08,6522.48,6530.21,6535.96,6540.25,8327.53,6728.01,5306.07,4116.61,3157.87,2403.31,1818.79,1370.89,1030.27,772.64,578.527,432.684,323.332,241.464,180.242,134.495,100.334,74.835,55.8085,41.615 +26369.1,0,14.3855,0,1,1,-26368.3,3.62823,5.35592,4.51241,0.0525888,7943.92,6572.58,5648.92,5017.2,4578.14,4268.51,4047.44,3888.02,3772.15,3687.41,3625.14,3579.23,3545.28,3520.13,3501.46,3487.59,3477.28,3469.61,3463.9,3459.65,44.9301,30.073,20.4044,14.0705,9.85456,6.99554,5.02152,3.63669,2.65212,1.9445,1.43153,1.05717,0.782539,0.580278,0.430866,0.320245,0.238202,0.177275,0.131986,0.0982996,2011.15,3397.35,4330.67,4968.73,5412,5724.49,5947.54,6108.34,6225.2,6310.65,6373.43,6419.72,6453.94,6479.29,6498.11,6512.08,6522.48,6530.21,6535.96,6540.25,8327.53,6728.01,5306.07,4116.61,3157.87,2403.31,1818.79,1370.89,1030.27,772.64,578.527,432.684,323.332,241.464,180.242,134.495,100.334,74.835,55.8085,41.615 +26369.1,0,2.43117,0,1,1,-26365.6,3.62823,5.35592,4.51241,0.0525888,7943.92,6572.58,5648.92,5017.2,4578.14,4268.51,4047.44,3888.02,3772.15,3687.41,3625.14,3579.23,3545.28,3520.13,3501.46,3487.59,3477.28,3469.61,3463.9,3459.65,44.9301,30.073,20.4044,14.0705,9.85456,6.99554,5.02152,3.63669,2.65212,1.9445,1.43153,1.05717,0.782539,0.580278,0.430866,0.320245,0.238202,0.177275,0.131986,0.0982996,2011.15,3397.35,4330.67,4968.73,5412,5724.49,5947.54,6108.34,6225.2,6310.65,6373.43,6419.72,6453.94,6479.29,6498.11,6512.08,6522.48,6530.21,6535.96,6540.25,8327.53,6728.01,5306.07,4116.61,3157.87,2403.31,1818.79,1370.89,1030.27,772.64,578.527,432.684,323.332,241.464,180.242,134.495,100.334,74.835,55.8085,41.615 +26369.1,0,0.239791,0,1,1,-26368.8,3.62823,5.35592,4.51241,0.0525888,7943.92,6572.58,5648.92,5017.2,4578.14,4268.51,4047.44,3888.02,3772.15,3687.41,3625.14,3579.23,3545.28,3520.13,3501.46,3487.59,3477.28,3469.61,3463.9,3459.65,44.9301,30.073,20.4044,14.0705,9.85456,6.99554,5.02152,3.63669,2.65212,1.9445,1.43153,1.05717,0.782539,0.580278,0.430866,0.320245,0.238202,0.177275,0.131986,0.0982996,2011.15,3397.35,4330.67,4968.73,5412,5724.49,5947.54,6108.34,6225.2,6310.65,6373.43,6419.72,6453.94,6479.29,6498.11,6512.08,6522.48,6530.21,6535.96,6540.25,8327.53,6728.01,5306.07,4116.61,3157.87,2403.31,1818.79,1370.89,1030.27,772.64,578.527,432.684,323.332,241.464,180.242,134.495,100.334,74.835,55.8085,41.615 +26369.1,0,0.0186273,0,1,1,-26368.1,3.62823,5.35592,4.51241,0.0525888,7943.92,6572.58,5648.92,5017.2,4578.14,4268.51,4047.44,3888.02,3772.15,3687.41,3625.14,3579.23,3545.28,3520.13,3501.46,3487.59,3477.28,3469.61,3463.9,3459.65,44.9301,30.073,20.4044,14.0705,9.85456,6.99554,5.02152,3.63669,2.65212,1.9445,1.43153,1.05717,0.782539,0.580278,0.430866,0.320245,0.238202,0.177275,0.131986,0.0982996,2011.15,3397.35,4330.67,4968.73,5412,5724.49,5947.54,6108.34,6225.2,6310.65,6373.43,6419.72,6453.94,6479.29,6498.11,6512.08,6522.48,6530.21,6535.96,6540.25,8327.53,6728.01,5306.07,4116.61,3157.87,2403.31,1818.79,1370.89,1030.27,772.64,578.527,432.684,323.332,241.464,180.242,134.495,100.334,74.835,55.8085,41.615 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+30685.1,0.816807,0.702592,2,3,0,-30682.3,1.02074,0.200005,10.0811,0.343027,9570.77,9121.81,8550.12,7876.97,7155.15,6452.92,5829.47,5317.54,4922.16,4630.28,4421.52,4275.43,4174.67,4105.85,4059.16,4027.62,4006.37,3992.09,3982.5,3976.06,218.976,302.984,389.546,463.085,503.455,498.733,452.311,379.816,299.615,225.279,163.511,115.723,80.4701,55.2801,37.6614,25.514,17.2189,11.591,7.78912,5.22821,210.256,575.209,1060.34,1659.94,2341.39,3048.35,3718.22,4302.65,4778.22,5144.44,5414.97,5608.85,5744.86,5838.87,5903.18,5946.87,5976.41,5996.32,6009.71,6018.71,5760.34,7899.28,10401.2,12745.8,14354.1,14763.7,13889.9,12055.4,9777.09,7514.37,5545.17,3972.31,2786.08,1925.46,1317.23,894.887,605.103,407.856,274.317,184.235 +30684.1,0.95441,0.702592,2,3,0,-30683.9,1.06729,0.186879,10.0022,0.377223,9575.57,9137.73,8574.19,7903.27,7176.15,6462.15,5823.62,5296.56,4888.06,4585.77,4369.21,4217.44,4112.63,4040.97,3992.29,3959.36,3937.15,3922.2,3912.15,3905.4,223.381,311.884,405.908,489.04,539.037,541.058,496.517,421.128,334.923,253.467,184.914,131.403,91.6713,63.1434,43.1156,29.2663,19.786,13.3405,8.97835,6.03515,201.05,550.382,1019.9,1607.69,2284.82,2996.79,3679.86,4282.32,4777.02,5160.76,5445.88,5651.16,5795.7,5895.89,5964.6,6011.38,6043.07,6064.46,6078.87,6088.57,5338.5,7388.45,9825.06,12167.8,13850.2,14389.1,13657.2,11940.9,9741.66,7522.41,5571.97,4003.67,2815.2,1949.81,1336.43,909.504,615.969,415.806,280.068,188.36 +# +# Elapsed Time: 21.2414 seconds (Warm-up) +# 3.57919 seconds (Sampling) +# 24.8206 seconds (Total) +# diff --git a/examples/sir/run_model.sh b/examples/sir/run_model.sh new file mode 100755 index 0000000000..f32729abab --- /dev/null +++ b/examples/sir/run_model.sh @@ -0,0 +1,6 @@ +#/bin/bash + +./sir sample save_warmup=1 algorithm=hmc metric=dense_e adapt delta=0.95 data file=sir.data.R output file=$1.output.csv id=$1 random seed=55781900 + +# run in parallel +# seq 4 | parallel -j 4 --workdir $PWD ./run_model.sh {} ::: 0 1 2 3 diff --git a/examples/sir/sir.data.R b/examples/sir/sir.data.R new file mode 100644 index 0000000000..b8958a4351 --- /dev/null +++ b/examples/sir/sir.data.R @@ -0,0 +1,12 @@ +N_t <- 20 + +t <- c(7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77, 84, 91, 98, 105, 112, 119, 126, 133,140) +y0 <- c(10000, 0, 0, 10000) + +stoi_hat <- c( +441, 419, 553, 666, 753, 692, 644, 509, 371, 286, 200, 147, 101, 68, 49, 35, 19, 12, 7, 10) + +B_hat <- c( + 6141.730, 5801.720, 9439.140, 13742.000, 11975.000, 16387.000, 15144.000, +14705.600, 8736.390, 7553.290, 6007.090, 5979.960, 3048.170, 1566.770, + 1275.210, 824.850, 604.605, 516.250, 258.046, 188.591) diff --git a/examples/sir/sir.stan b/examples/sir/sir.stan new file mode 100644 index 0000000000..07a11bcb08 --- /dev/null +++ b/examples/sir/sir.stan @@ -0,0 +1,69 @@ +// Simple SIR model inspired by the presentation in +// http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3380087/pdf/nihms372789.pdf + +functions { + // theta[1] = beta, water contact rate + // theta[2] = kappa, C_{50} + // theta[3] = gamma, recovery rate + // theta[4] = xi, bacteria production rate + // theta[5] = delta, bacteria removal rate + real[] simple_SIR(real t, + real[] y, + real[] theta, + real[] x_r, + int[] x_i) { + + real dydt[4]; + + dydt[1] = - theta[1] * y[4] / (y[4] + theta[2]) * y[1]; + dydt[2] = theta[1] * y[4] / (y[4] + theta[2]) * y[1] - theta[3] * y[2]; + dydt[3] = theta[3] * y[2]; + dydt[4] = theta[4] * y[2] - theta[5] * y[4]; + + return dydt; + } +} + +data { + int N_t; + real t[N_t]; + real y0[4]; + int stoi_hat[N_t]; + real B_hat[N_t]; +} + +transformed data { + real t0 = 0; + real kappa = 1000000; + + real x_r[0]; + int x_i[0]; +} + +parameters { + real beta; + real gamma; + real xi; + real delta; +} + +transformed parameters { + real y[N_t, 4]; + { + real theta[5] = {beta, kappa, gamma, xi, delta}; + y = integrate_ode_rk45(simple_SIR, y0, t0, t, theta, x_r, x_i); + } +} + +model { + beta ~ cauchy(0, 2.5); + gamma ~ cauchy(0, 1); + xi ~ cauchy(0, 25); + delta ~ cauchy(0, 1); + + stoi_hat[1] ~ poisson(y0[1] - y[1, 1]); + for (n in 2:N_t) + stoi_hat[n] ~ poisson(y[n - 1, 1] - y[n, 1]); + + B_hat ~ lognormal(log(col(to_matrix(y), 4)), 0.15); +} diff --git a/make/mpi_warmup.mk b/make/mpi_warmup.mk new file mode 100644 index 0000000000..7b047a025a --- /dev/null +++ b/make/mpi_warmup.mk @@ -0,0 +1,5 @@ +ifdef MPI_ADAPTED_WARMUP + CXXFLAGS += -DSTAN_LANG_MPI -DMPI_ADAPTED_WARMUP + CC=mpicxx + CXX=mpicxx +endif diff --git a/makefile b/makefile index 43203461e8..b97e04bafd 100644 --- a/makefile +++ b/makefile @@ -20,6 +20,7 @@ help: -include $(HOME)/.config/stan/make.local # user-defined variables -include make/local # user-defined variables +-include make/mpi_warmup.mk STAN ?= stan/ MATH ?= $(STAN)lib/stan_math/ diff --git a/src/cmdstan/arguments/arg_adapt.hpp b/src/cmdstan/arguments/arg_adapt.hpp index 50457d94a1..49679d2a16 100644 --- a/src/cmdstan/arguments/arg_adapt.hpp +++ b/src/cmdstan/arguments/arg_adapt.hpp @@ -10,6 +10,10 @@ #include #include #include +#include +#include +#include +#include namespace cmdstan { class arg_adapt: public categorical_argument { @@ -26,6 +30,10 @@ namespace cmdstan { _subarguments.push_back(new arg_adapt_init_buffer()); _subarguments.push_back(new arg_adapt_term_buffer()); _subarguments.push_back(new arg_adapt_window()); + _subarguments.push_back(new arg_adapt_num_cross_chains()); + _subarguments.push_back(new arg_adapt_cross_chain_window()); + _subarguments.push_back(new arg_adapt_cross_chain_rhat()); + _subarguments.push_back(new arg_adapt_cross_chain_ess()); } }; diff --git a/src/cmdstan/arguments/arg_adapt_cross_chain_ess.hpp b/src/cmdstan/arguments/arg_adapt_cross_chain_ess.hpp new file mode 100644 index 0000000000..159650e547 --- /dev/null +++ b/src/cmdstan/arguments/arg_adapt_cross_chain_ess.hpp @@ -0,0 +1,20 @@ +#ifndef CMDSTAN_ARGUMENTS_ARG_ADAPT_CROSS_CHAIN_ESS_HPP +#define CMDSTAN_ARGUMENTS_ARG_ADAPT_CROSS_CHAIN_ESS_HPP + +#include + +namespace cmdstan { + + class arg_adapt_cross_chain_ess: public u_int_argument { + public: + arg_adapt_cross_chain_ess(): u_int_argument() { + _name = "cross_chain_ess"; + _description = "Target ESS for cross-chain warmup"; + _default = "200"; + _default_value = 200; + _value = _default_value; + } + }; + +} +#endif diff --git a/src/cmdstan/arguments/arg_adapt_cross_chain_rhat.hpp b/src/cmdstan/arguments/arg_adapt_cross_chain_rhat.hpp new file mode 100644 index 0000000000..bb5ee8bda2 --- /dev/null +++ b/src/cmdstan/arguments/arg_adapt_cross_chain_rhat.hpp @@ -0,0 +1,27 @@ +#ifndef CMDSTAN_ARGUMENTS_ARG_ADAPT_CROSS_CHAIN_RHAT_HPP +#define CMDSTAN_ARGUMENTS_ARG_ADAPT_CROSS_CHAIN_RHAT_HPP + +#include + +namespace cmdstan { + + class arg_adapt_cross_chain_rhat: public real_argument { + public: + arg_adapt_cross_chain_rhat(): real_argument() { + _name = "cross_chain_rhat"; + _description = "Target Rhat for cross-chain warmup"; + _validity = "0.8 < cross_chain_rhat"; + _default = "1.05"; + _default_value = 1.05; + _constrained = true; + _good_value = 2.0; + _bad_value = -1.0; + _value = _default_value; + } + + bool is_valid(double value) { return value > 0.8; } +}; + + +} +#endif diff --git a/src/cmdstan/arguments/arg_adapt_cross_chain_window.hpp b/src/cmdstan/arguments/arg_adapt_cross_chain_window.hpp new file mode 100644 index 0000000000..1a313ce25e --- /dev/null +++ b/src/cmdstan/arguments/arg_adapt_cross_chain_window.hpp @@ -0,0 +1,20 @@ +#ifndef CMDSTAN_ARGUMENTS_ARG_ADAPT_CROSS_CHAIN_WINDOW_HPP +#define CMDSTAN_ARGUMENTS_ARG_ADAPT_CROSS_CHAIN_WINDOW_HPP + +#include + +namespace cmdstan { + + class arg_adapt_cross_chain_window: public u_int_argument { + public: + arg_adapt_cross_chain_window(): u_int_argument() { + _name = "cross_chain_window"; + _description = "Window size for cross-chain warmup"; + _default = "100"; + _default_value = 100; + _value = _default_value; + } + }; + +} +#endif diff --git a/src/cmdstan/arguments/arg_adapt_num_cross_chains.hpp b/src/cmdstan/arguments/arg_adapt_num_cross_chains.hpp new file mode 100644 index 0000000000..cfeaedcf18 --- /dev/null +++ b/src/cmdstan/arguments/arg_adapt_num_cross_chains.hpp @@ -0,0 +1,43 @@ +#ifndef CMDSTAN_ARGUMENTS_ARG_ADAPT_NUM_CROSS_CHAIN_HPP +#define CMDSTAN_ARGUMENTS_ARG_ADAPT_NUM_CROSS_CHAIN_HPP + +#include +#ifdef MPI_ADAPTED_WARMUP +#include +#endif + +namespace cmdstan { + + class arg_adapt_num_cross_chains: public u_int_argument { + public: + arg_adapt_num_cross_chains(): u_int_argument() { + _name = "num_cross_chains"; + _description = "Number of chains in cross-chain warmup iterations"; +#ifdef MPI_ADAPTED_WARMUP + _validity = "num_cross_chains <= number of MPI processes"; + _default = "number of MPI processes"; + int stan_world_size; + MPI_Comm_size(MPI_COMM_STAN, &stan_world_size); + _default_value = stan_world_size; + _constrained = true; + _good_value = 2; + _bad_value = -1; +#else + _validity = "0 < num_cross_chains"; + _default = "1"; + _default_value = 1; +#endif + _value = _default_value; + } + +#ifdef MPI_ADAPTED_WARMUP + bool is_valid(unsigned int value) { + int stan_world_size; + MPI_Comm_size(MPI_COMM_STAN, &stan_world_size); + return value <= stan_world_size; + } +#endif + }; + +} +#endif diff --git a/src/cmdstan/arguments/arg_num_warmup.hpp b/src/cmdstan/arguments/arg_num_warmup.hpp index 4656af835c..7e6a0a488b 100644 --- a/src/cmdstan/arguments/arg_num_warmup.hpp +++ b/src/cmdstan/arguments/arg_num_warmup.hpp @@ -8,8 +8,13 @@ namespace cmdstan { class arg_num_warmup: public int_argument { public: arg_num_warmup(): int_argument() { +#ifdef MPI_ADAPTED_WARMUP + _name = "max_num_warmup"; + _description = "Maximum number of warmup iterations"; +#else _name = "num_warmup"; _description = "Number of warmup iterations"; +#endif _validity = "0 <= warmup"; _default = "1000"; _default_value = 1000; diff --git a/src/cmdstan/command.hpp b/src/cmdstan/command.hpp index 4a5024ea54..d49a89b9fb 100644 --- a/src/cmdstan/command.hpp +++ b/src/cmdstan/command.hpp @@ -14,6 +14,7 @@ #include #include #include +#include #include #include #include @@ -37,6 +38,7 @@ #include #include #include +#include #include #include #include @@ -95,8 +97,13 @@ namespace cmdstan { int command(int argc, const char* argv[]) { +#ifdef MPI_ADAPTED_WARMUP + stan::callbacks::mpi_stream_writer info(1, std::cout); + stan::callbacks::mpi_stream_writer err(1, std::cout); +#else stan::callbacks::stream_writer info(std::cout); stan::callbacks::stream_writer err(std::cout); +#endif stan::callbacks::stream_logger logger(std::cout, std::cout, std::cout, std::cerr, std::cerr); @@ -131,21 +138,59 @@ namespace cmdstan { } else { random_seed = static_cast(random_arg->value()); } + + // number of chains for cross-chain warmup + unsigned int num_cross_chains = 0; + unsigned int cross_chain_window = 0; + double cross_chain_rhat = 0.0; + unsigned int cross_chain_ess = 0; +#ifdef MPI_ADAPTED_WARMUP + if (parser.arg("method")->arg("sample")) { + categorical_argument* adapt = dynamic_cast(parser.arg("method")->arg("sample")->arg("adapt")); + num_cross_chains = dynamic_cast(adapt->arg("num_cross_chains"))->value(); + cross_chain_window = dynamic_cast(adapt->arg("cross_chain_window"))->value(); + cross_chain_rhat = dynamic_cast(adapt->arg("cross_chain_rhat"))->value(); + cross_chain_ess = dynamic_cast(adapt->arg("cross_chain_ess"))->value(); + + if (num_cross_chains > 1) { + int_argument* id_arg = dynamic_cast(parser.arg("id")); + unsigned int id = id_arg->value(); + stan::services::util::set_cross_chain_id(id, num_cross_chains); + id_arg -> set_value(static_cast(id)); + + string_argument* ptr_out = dynamic_cast(parser.arg("output")->arg("file")); + std::string f_out = ptr_out -> value(); + stan::services::util::set_cross_chain_file(f_out, num_cross_chains); + ptr_out -> set_value(f_out); + + info.set_num_chains(num_cross_chains); + err.set_num_chains(num_cross_chains); + } + } +#endif + parser.print(info); info(); stan::callbacks::writer init_writer; stan::callbacks::interrupt interrupt; - std::fstream output_stream(dynamic_cast(parser.arg("output")->arg("file"))->value().c_str(), std::fstream::out); +#ifdef MPI_ADAPTED_WARMUP + stan::callbacks::mpi_stream_writer sample_writer(num_cross_chains, output_stream, "# "); +#else stan::callbacks::stream_writer sample_writer(output_stream, "# "); +#endif + std::fstream diagnostic_stream(dynamic_cast(parser.arg("output")->arg("diagnostic_file"))->value().c_str(), std::fstream::out); +#ifdef MPI_ADAPTED_WARMUP + stan::callbacks::mpi_stream_writer diagnostic_writer(num_cross_chains, diagnostic_stream, "# "); +#else stan::callbacks::stream_writer diagnostic_writer(diagnostic_stream, "# "); - +#endif ////////////////////////////////////////////////// // Initialize Model // @@ -320,8 +365,14 @@ namespace cmdstan { sample_writer); } } else if (parser.arg("method")->arg("sample")) { +#ifdef MPI_ADAPTED_WARMUP + int num_warmup = + dynamic_cast(parser.arg("method")->arg("sample")->arg("max_num_warmup"))->value(); +#else int num_warmup = dynamic_cast(parser.arg("method")->arg("sample")->arg("num_warmup"))->value(); +#endif int num_samples = dynamic_cast(parser.arg("method")->arg("sample")->arg("num_samples"))->value(); + int num_thin = dynamic_cast(parser.arg("method")->arg("sample")->arg("thin"))->value(); bool save_warmup = dynamic_cast(parser.arg("method")->arg("sample")->arg("save_warmup"))->value(); list_argument* algo = dynamic_cast(parser.arg("method")->arg("sample")->arg("algorithm")); @@ -417,6 +468,10 @@ namespace cmdstan { random_seed, id, init_radius, + num_cross_chains, + cross_chain_window, + cross_chain_rhat, + cross_chain_ess, num_warmup, num_samples, num_thin, @@ -452,6 +507,10 @@ namespace cmdstan { random_seed, id, init_radius, + num_cross_chains, + cross_chain_window, + cross_chain_rhat, + cross_chain_ess, num_warmup, num_samples, num_thin, @@ -530,6 +589,10 @@ namespace cmdstan { random_seed, id, init_radius, + num_cross_chains, + cross_chain_window, + cross_chain_rhat, + cross_chain_ess, num_warmup, num_samples, num_thin, @@ -566,6 +629,10 @@ namespace cmdstan { random_seed, id, init_radius, + num_cross_chains, + cross_chain_window, + cross_chain_rhat, + cross_chain_ess, num_warmup, num_samples, num_thin, @@ -619,6 +686,10 @@ namespace cmdstan { random_seed, id, init_radius, + num_cross_chains, + cross_chain_window, + cross_chain_rhat, + cross_chain_ess, num_warmup, num_samples, num_thin, diff --git a/stan b/stan index 37fbc8fbfb..405266debd 160000 --- a/stan +++ b/stan @@ -1 +1 @@ -Subproject commit 37fbc8fbfb55c2f7f7970ee08e236e826cb34bf8 +Subproject commit 405266debdc8713eb6713851a00415465d85ea39