Results

docs/.documenter-siteinfo.json

@@ -1 +1 @@
-{"documenter":{"julia_version":"1.10.2","generation_timestamp":"2024-05-16T12:44:20","documenter_version":"1.4.1"}}
+{"documenter":{"julia_version":"1.10.2","generation_timestamp":"2024-05-17T06:57:50","documenter_version":"1.4.1"}}

docs/arK_model/Moments.csv

@@ -1,8 +1,8 @@
 parameters,mean,std,mcse,ess_bulk,ess_tail,rhat,ess_per_sec
-alpha,-0.0007419440021482449,0.010845124623626958,0.00011774207865860055,8466.148895902883,10794.473564621916,1.0000224681096204,
-beta.1,0.6902675613644529,0.07105091934898923,0.0011704211801884265,3695.8268117563302,4997.100993796854,1.0004649755956627,
-beta.2,0.44163364721116194,0.08829286632002908,0.0014027899594256852,3965.9154525927697,4754.886259371885,1.0003774687589715,
-beta.3,0.10586155854262908,0.09131014874978582,0.0014173278313273068,4152.291426021026,5790.06394727355,1.0000251499841275,
-beta.4,-0.037215974910460456,0.08747507638921705,0.0013990186777859772,3939.3432593810758,5084.06707876355,1.0000445345026796,
-beta.5,-0.30087252062085806,0.0705391942487051,0.001202917551610419,3455.4077227252624,4362.425380378789,1.0000368212646813,
-sigma,0.15068165630119562,0.00788278490080416,0.00010294442401837485,5922.934677290424,7822.99976055058,1.0001713659227789,
+alpha,-0.0008169068872928797,0.010793726913744599,4.156753890570419e-5,67439.6347751395,78648.63397123425,1.000132780925467,
+beta.1,0.6909176443616998,0.07101201332647641,0.00047773128692869826,22156.918346904757,27971.290560474208,1.000194968335765,
+beta.2,0.4414819148644378,0.08693680959712055,0.000577236203001733,22837.257858253186,27995.13955068914,1.0001129530890651,
+beta.3,0.10478133091132097,0.09232736634213422,0.000579068488654412,25453.648962340267,35754.78372800737,1.000013736969468,
+beta.4,-0.03669417053262631,0.08558537860558647,0.0005485172933069619,24395.832876455806,31185.830164211053,1.0000033324621405,
+beta.5,-0.3005920745733407,0.07009561198103649,0.00045677435970731744,23600.503942648746,31262.80366374732,0.9999985416006273,
+sigma,0.15049230600705524,0.007817427596097453,4.065629532187205e-5,37151.33520641205,53528.95925050927,1.000001142959893,

docs/arK_model/Pigeons_inputs.csv

@@ -5,13 +5,13 @@ extractor,nothing
 record,"Function[Pigeons.traces, Pigeons.round_trip, Pigeons.log_sum_ratio, Pigeons.timing_extrema, Pigeons.allocation_extrema]"
 multithreaded,false
 show_report,true
-n_chains,20
-variational,"GaussianReference(Dict{Symbol, Any}(:singleton_variable => [-0.0007419440021482451, 0.690267561364453, 0.441633647211162, 0.10586155854262908, -0.03721597491046045, -0.30087252062085806, -1.8939465139879277]), Dict{Symbol, Any}(:singleton_variable => [0.010845124623626958, 0.07105091934898923, 0.08829286632002906, 0.09131014874978584, 0.08747507638921706, 0.0705391942487051, 0.052109994777569286]), 12)"
+n_chains,10
+variational,"GaussianReference(Dict{Symbol, Any}(), Dict{Symbol, Any}(), 15)"
 explorer,nothing
 n_chains_variational,0
 target,StanLogPotential(arK_model)
-n_rounds,14
-exec_folder,nothing
+n_rounds,17
+exec_folder,/scratch/st-alexbou-1/abc/InferHub-infra/work/76/97f2112331d6cbc51f391c2600f6a6/results/all/2024-05-16-15-18-13-KFWqxY88
 reference,nothing
-checkpoint,false
+checkpoint,true
 seed,1

docs/arK_model/Pigeons_summary.csv

@@ -1,15 +1,18 @@
 round,n_scans,n_tempered_restarts,global_barrier,global_barrier_variational,last_round_max_time,last_round_max_allocation,stepping_stone
-1,2,0,1.4432899320127035e-14,,1.188333498,3.240272e7,-9.2148511043888e-15
-2,4,0,1.6431300764452317e-14,,0.408015707,97888.0,-3.1086244689504383e-15
-3,8,0,1.0658141036401503e-14,,0.812150093,192400.0,5.329070518200751e-15
-4,16,0,3.552713678800501e-15,,1.758136957,407520.0,8.881784197001252e-16
-5,32,7,2.5757174171303632e-14,,3.491972248,645184.0,6.439293542825908e-15
-6,64,23,2.7533531010703882e-14,,7.274139905,829760.0,-1.3322676295501878e-15
-7,128,55,9.658940314238862e-15,,14.549662682,1.08576e6,4.440892098500626e-16
-8,256,119,1.1879386363489175e-14,,28.137201056,1.6336e6,8.881784197001252e-16
-9,512,247,1.2545520178264269e-14,,56.873878178,2.62176e6,1.7763568394002505e-15
-10,1024,503,1.3766765505351941e-14,,114.345735644,4.80448e6,0.0
-11,2048,1015,1.2545520178264269e-14,,227.068526136,8.76576e6,-8.881784197001252e-16
-12,4096,2039,3.097522238704187e-14,,456.979478453,1.747616e7,-1.3322676295501878e-15
-13,8192,1298,1.5270631712091665,,489.01428968,9.941790968e9,57.90689728683546
-14,16384,2956,1.5678161953018974,,986.740654173,2.074180256e10,57.90354387257936
+1,2,0,0.0,,0.718631931,5.125064e7,-3.9968028886505635e-15
+2,4,0,1.2434497875801753e-14,,1.046206457,5.2965144e7,0.0
+3,8,0,0.0,,0.240224647,91888.0,0.0
+4,16,4,1.0658141036401503e-14,,0.38065737,160176.0,2.6645352591003757e-15
+5,32,12,0.0,,0.769243981,234128.0,6.661338147750939e-16
+6,64,28,6.661338147750939e-16,,1.530114791,396272.0,-1.3322676295501878e-15
+7,128,60,5.10702591327572e-15,,2.993500132,732944.0,0.0
+8,256,124,8.326672684688674e-15,,5.814287882,1.355856e6,4.440892098500626e-16
+9,512,252,4.6629367034256575e-15,,11.479289872,2.666368e6,0.0
+10,1024,508,1.2545520178264269e-14,,23.187533263,5.205488e6,4.440892098500626e-16
+11,2048,1020,1.3211653993039363e-14,,48.186338785,1.0472016e7,-4.440892098500626e-16
+12,4096,2044,1.1657341758564144e-14,,93.25757241,2.059272e7,0.0
+13,8192,4092,1.9317880628477724e-14,,183.538472968,4.1619856e7,0.0
+14,16384,8188,1.1102230246251565e-14,,364.433900941,8.2152944e7,1.7763568394002505e-15
+15,32768,16380,7.771561172376096e-15,,742.719338759,1.66286368e8,8.881784197001252e-16
+16,65536,9164,1.467393100573205,,854.944313996,2.1429932704e10,57.99222434777241
+17,131072,21522,1.5557124764543793,,1781.663863431,4.4490783776e10,57.8922194952098

docs/arK_model/info.json

@@ -1,7 +1,7 @@
 {
     "target_name": "arK_model",
     "original_dim": 7,
-    "gcb": 1.5678161953018974,
-    "logz": 57.90354387257936,
+    "gcb": 1.5557124764543793,
+    "logz": 57.8922194952098,
     "bibliography": "@misc{furr2016hier,\n  title={Hierarchical two-parameter logistic item response model},\n  url={https://mc-stan.org/users/documentation/case-studies/hierarchical_2pl.html},\n  author={Furr, Daniel},\n  year={2016},\n  month={Apr}\n}\n\n@book{kery2011population,\n  title={Bayesian population analysis using WinBUGS},\n  author={M Kery, M Schaub},\n  year={2011},\n  publisher={Academic Press}\n}\n\n@book{lee2013cognitive,\n  title={Bayesian Cognitive Modeling},\n  author={M D Lee, E Wagenmakers},\n  year={2013},\n  publisher={Cambridge University Press}\n}\n\n@article{glas2003computerized,\n  title={Computerized adaptive testing with item cloning},\n  author={Glas, Cees AW and van der Linden, Wim J},\n  journal={Applied Psychological Measurement},\n  volume={27},\n  number={4},\n  pages={247--261},\n  year={2003},\n  publisher={Sage Publications}\n}\n\n@article{dorazio2006estimating,\n  title={Estimating species richness and accumulation by modeling species occurrence and detectability},\n  author={Dorazio, Robert M and Royle, J Andrew and S{\\\"o}derstr{\\\"o}m, Bo and Glimsk{\\\"a}r, Anders},\n  journal={Ecology},\n  volume={87},\n  number={4},\n  pages={842--854},\n  year={2006},\n  publisher={Wiley Online Library}\n}\n\n@article{sierra2014modeling,\n  title={Modeling radiocarbon dynamics in soils: SoilR version 1.1},\n  author={Sierra, Carlos and M{\\\"u}ller, Markus and Trumbore, Susan E},\n  journal={Geoscientific Model Development},\n  volume={7},\n  number={5},\n  pages={1919--1931},\n  year={2014},\n  publisher={Copernicus Publ.}\n}\n\n@article{hewitt1921conservation,\n  title={The Conservation of thc Wild Life of Canada},\n  author={Hewitt, CG},\n  journal={New Yorli},\n  year={1921}\n}\n\n@misc{howard2009modeling,\n  author={Howard, Peter},\n  title={Modeling basics, Lecture Notes for Math 442},\n  year={2009},\n  publisher={Texas A&M University}\n}\n\n@article{lotka1925principles,\n  title={Principles of physical biology},\n  author={Lotka, AJ},\n  journal={Baltimore: Waverly},\n  year={1925}\n}\n\n@misc{volterra1926fluctuations,\n  title={Fluctuations in the abundance of a species considered mathematically},\n  author={Volterra, Vito},\n  year={1926},\n  publisher={Nature Publishing Group}\n}\n\n@book{volterra1927variazioni,\n  title={Variazioni e fluttuazioni del numero d'individui in specie animali conviventi},\n  author={Volterra, Vito},\n  year={1927},\n  publisher={C. Ferrari}\n}\n\n@article{li2018feature,\n  title={Feature selection: A data perspective},\n  author={Li, Jundong and Cheng, Kewei and Wang, Suhang and Morstatter, Fred and Trevino, Robert P and Tang, Jiliang and Liu, Huan},\n  journal={ACM Computing Surveys (CSUR)},\n  volume={50},\n  number={6},\n  pages={94},\n  year={2018},\n  publisher={ACM}\n}\n\n@article{piironen2017sparsity,\n  title={Sparsity information and regularization in the horseshoe and other shrinkage priors},\n  author={Piironen, Juho and Vehtari, Aki and others},\n  journal={Electronic Journal of Statistics},\n  volume={11},\n  number={2},\n  pages={5018--5051},\n  year={2017},\n  publisher={The Institute of Mathematical Statistics and the Bernoulli Society}\n}\n\n@article{taylor2018forecasting,\n  title={Forecasting at scale},\n  author={Taylor, Sean J and Letham, Benjamin},\n  journal={The American Statistician},\n  volume={72},\n  number={1},\n  pages={37--45},\n  year={2018},\n  publisher={Taylor \\& Francis}\n}\n\n@article{bales2019selecting,\n  title={Selecting the Metric in Hamiltonian Monte Carlo},\n  author={Bales, Ben and Pourzanjani, Arya and Vehtari, Aki and Petzold, Linda},\n  journal={arXiv preprint arXiv:1905.11916},\n  year={2019}\n}\n\n@book{wickham2016ggplot2,\n  title={ggplot2: elegant graphics for data analysis},\n  author={Wickham, Hadley},\n  year={2016},\n  publisher={Springer}\n}\n\n@book{venables2013modern,\n  title={Modern applied statistics with S-PLUS},\n  author={Venables, William N and Ripley, Brian D},\n  year={2013},\n  publisher={Springer Science \\& Business Media}\n}\n\n@book{gelman2006data,\n  title={Data analysis using regression and multilevel/hierarchical models},\n  author={Gelman, Andrew and Hill, Jennifer},\n  year={2006},\n  publisher={Cambridge university press}\n}\n\n@book{gelman2013bayesian,\n  title={Bayesian data analysis},\n  author={Gelman, Andrew and Carlin, John B and Stern, Hal S and Dunson, David B and Vehtari, Aki and Rubin, Donald B},\n  year={2013},\n  publisher={Chapman and Hall/CRC}\n}\n\n@article{rubin1981estimation,\n  title={Estimation in parallel randomized experiments},\n  author={Rubin, Donald B},\n  journal={Journal of Educational Statistics},\n  volume={6},\n  number={4},\n  pages={377--401},\n  year={1981},\n  publisher={Sage Publications Sage CA: Thousand Oaks, CA}\n}\n\n@article{blei2003latent,\n  title={Latent dirichlet allocation},\n  author={Blei, David M and Ng, Andrew Y and Jordan, Michael I},\n  journal={Journal of machine Learning research},\n  volume={3},\n  number={Jan},\n  pages={993--1022},\n  year={2003}\n}\n\n@article{grad2012cholera,\n  title={Cholera modeling: challenges to quantitative analysis and predicting the impact of interventions},\n  author={Grad, Yonatan H and Miller, Joel C and Lipsitch, Marc},\n  journal={Epidemiology (Cambridge, Mass.)},\n  volume={23},\n  number={4},\n  pages={523},\n  year={2012},\n  publisher={NIH Public Access}\n}\n\n@TechReport{flaxman2020report,\n  title={Report 13: Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in 11 European countries},\n  author={Flaxman, Seth and Mishra, Swapnil and Gandy, Axel and Unwin, H and Coupland, H and Mellan, T and Zhu, H and Berah, T and Eaton, J and Perez Guzman, P and others},\n  institution = {Imperial College London},\n  year={2020}\n}\n\n@article{lecun1998gradient,\n  title={Gradient-based learning applied to document recognition},\n  author={LeCun, Yann and Bottou, L{\\'e}on and Bengio, Yoshua and Haffner, Patrick},\n  journal={Proceedings of the IEEE},\n  volume={86},\n  number={11},\n  pages={2278--2324},\n  year={1998},\n  publisher={Ieee}\n}\n\n@article{lampinen2001bayesian,\n  title={Bayesian approach for neural networks—review and case studies},\n  author={Lampinen, Jouko and Vehtari, Aki},\n  journal={Neural networks},\n  volume={14},\n  number={3},\n  pages={257--274},\n  year={2001},\n  publisher={Elsevier}\n}\n\n@misc{jonasson2021rapid,\n  Author = {Johan Jonasson and Måns Magnusson},\n  Title = {Rapid mixing in unimodal landscapes and efficient simulated annealing for multimodal distributions},\n  Year = {2021},\n  Eprint = {arXiv:2101.10004},\n}\n\n@misc{farkas2014threemen,\n  Author = {Andras Farkas},\n  Title = {Three Men and a Boat, translated by Andras Farkas to French and Swedish},\n  url = {FarkasTranslations.com},\n  Year = {2014},\n}\n\n@misc{reif2008bird,\n  Author = {Jil{\\'i} Reif and David Storch and Petr Vol{\\'i}nek and Karel Kpastn{\\'y} and Vladim{\\'i}r Bejbek},\n  Title = {Bird-habitat associations predict population trends in central European forest and farmland birds},\n  url = {https://link.springer.com/article/10.1007/s10531-008-9430-4},\n  Year = {2008},\n}\n\n@article{dimaggio2015small,\n  title={Small-area spatiotemporal analysis of pedestrian and bicyclist injuries in {New York City}},\n  author={DiMaggio, Charles},\n  journal={Epidemiology},\n  volume={26},\n  number={2},\n  pages={247--254},\n  year={2015},\n  publisher={JSTOR}\n}\n\n@article{flaxman2015fast,\n  title={Fast hierarchical Gaussian processes},\n  author={Flaxman, Seth and Gelman, Andrew and Neill, Daniel and Smola, Alex and Vehtari, Aki and Wilson, Andrew Gordon},\n  journal={Manuscript in preparation},\n  year={2015}\n}\n\n@book{reif1995euro,\n  title={Euro-barometer 38.1: Consumer protection and perceptions of science and technology, november 1992},\n  author={Reif, Karlheinz and Melich, Anna},\n  year={1995},\n  publisher={Inter-university Consortium for Political and Social Research}\n}\n\n@misc{mrc1winbugs,\n  Author = {MRC Biostatistics Unit},\n  Title = {Examples Volume 1},\n  url = {http://www.mrc-bsu.cam.ac.uk/wp-content/uploads/WinBUGS_Vol1.pdf},\n}\n\n@misc{mrc2winbugs,\n  Author = {MRC Biostatistics Unit},\n  Title = {Examples Volume 2},\n  url = {http://www.mrc-bsu.cam.ac.uk/wp-content/uploads/WinBUGS_Vol2.pdf},\n}\n\n@article{roche1975rwt,\n  author = {Alex F. Roche and Howard Wainer and David Thissen},\n  title = {The RWT Method for the Prediction of Adult Stature},\n  journal = {Official Journal of the American Academy of Pediatrics},\n  year = {1975},\n  volume = {56},\n  number = {6},\n  pages = {1026--1033},\n  publisher = {American Academy of Pediatrics}\n}\n\n@article{gelfand1990illustration,\n  author = {Alan E. Gelfand and Susan E. Hills and Amy Racine-Poon and Adrian F. M. Smith},\n  title = {Illustration of Bayesian Inference in Normal Data Models Using Gibbs Sampling},\n  journal = {Journal of the American Statistical Association},\n  volume = {85},\n  number = {412},\n  pages = {972-985},\n  year  = {1990},\n  publisher = {Taylor & Francis},\n  doi = {10.1080/01621459.1990.10474968},\n  URL = {https://www.tandfonline.com/doi/abs/10.1080/01621459.1990.10474968},\n  eprint = {https://www.tandfonline.com/doi/pdf/10.1080/01621459.1990.10474968}\n}\n\n@article{crowder1978beta,\n  author = {Martin J. Crowder},\n  title = {Beta-Binomial Anova for Proportions},\n  journal = {Journal of the Royal Statistical Society: Series C (Applied Statistics)},\n  volume = {27},\n  number = {1},\n  pages = {34-37},\n  keywords = {anova for proportions, beta-binomial distribution},\n  doi = {https://doi.org/10.2307/2346223},\n  url = {https://rss.onlinelibrary.wiley.com/doi/abs/10.2307/2346223},\n  eprint = {https://rss.onlinelibrary.wiley.com/doi/pdf/10.2307/2346223},\n  abstract = {Summary A method is proposed for the regression analysis of proportions based on the Beta-binomial distribution.},\n  year = {1978}\n}\n"
 }

docs/arma11_model/Moments.csv

@@ -1,5 +1,5 @@
 parameters,mean,std,mcse,ess_bulk,ess_tail,rhat,ess_per_sec
-mu,0.006995597187512798,0.0114112067547474,9.353875234098011e-5,14908.213001304299,15217.235228305623,1.0000014669639319,
-phi,0.9568151028095284,0.02307103479758951,0.0001974781993756645,13692.075042409348,14220.653534616426,0.9999944456729835,
-theta,-0.03360416392868518,0.05926610305955787,0.0005683547104118314,10874.16917881039,11929.071743094733,1.0000083728306108,
-sigma,0.16669478864584175,0.00851394845866245,7.699550176011778e-5,12225.71387877527,13272.337163138083,0.9999642840613713,
+mu,0.006842065494138883,0.011323747115820362,3.2290010853916653e-5,123051.45460502083,122449.9613121485,0.9999993514504437,
+phi,0.9567442730170562,0.022919614335558593,6.840678634596852e-5,112439.04193736902,115979.47705523157,1.0000067826022296,
+theta,-0.03363181469841902,0.05942795360861528,0.00019332432956870263,94588.63133067067,102176.6381882634,1.0000054753693983,
+sigma,0.16658001589857446,0.008499534440745289,2.7274800939263727e-5,97504.81726186266,103689.33756997733,1.0000020730815578,

docs/arma11_model/Pigeons_inputs.csv

@@ -5,13 +5,13 @@ extractor,nothing
 record,"Function[Pigeons.traces, Pigeons.round_trip, Pigeons.log_sum_ratio, Pigeons.timing_extrema, Pigeons.allocation_extrema]"
 multithreaded,false
 show_report,true
-n_chains,20
-variational,"GaussianReference(Dict{Symbol, Any}(:singleton_variable => [0.006995597187512798, 0.9568151028095284, -0.0336041639286852, -1.7928900673015136]), Dict{Symbol, Any}(:singleton_variable => [0.011411206754747402, 0.02307103479758951, 0.05926610305955788, 0.05094614412122614]), 12)"
+n_chains,10
+variational,"GaussianReference(Dict{Symbol, Any}(), Dict{Symbol, Any}(), 15)"
 explorer,nothing
 n_chains_variational,0
 target,StanLogPotential(arma11_model)
-n_rounds,14
-exec_folder,nothing
+n_rounds,17
+exec_folder,/scratch/st-alexbou-1/abc/InferHub-infra/work/b2/c2f2f251fa16e33cd1adf4e39a186b/results/all/2024-05-16-14-50-56-mhXFMlc7
 reference,nothing
-checkpoint,false
+checkpoint,true
 seed,1

docs/arma11_model/Pigeons_summary.csv

@@ -1,15 +1,18 @@
 round,n_scans,n_tempered_restarts,global_barrier,global_barrier_variational,last_round_max_time,last_round_max_allocation,stepping_stone
-1,2,0,1.0658141036401503e-14,,0.957903548,3.2399312e7,-1.7763568394002505e-14
-2,4,0,1.7763568394002505e-14,,0.244565088,96544.0,1.0658141036401503e-14
-3,8,0,8.881784197001252e-15,,0.401494199,190096.0,2.6645352591003757e-15
-4,16,0,1.1546319456101628e-14,,0.851811362,403296.0,-4.440892098500626e-16
-5,32,7,2.475797344914099e-14,,1.714355989,637120.0,-2.220446049250313e-16
-6,64,23,9.769962616701378e-15,,3.543320161,819008.0,1.5543122344752192e-15
-7,128,55,1.63202784619898e-14,,7.113963706,1.071936e6,-8.881784197001252e-16
-8,256,119,2.1316282072803006e-14,,14.255183999,1.613632e6,-8.881784197001252e-16
-9,512,247,2.5091040356528538e-14,,28.488016973,2.589504e6,1.3322676295501878e-15
-10,1024,503,3.863576125695545e-14,,56.862558354,4.747648e6,-8.881784197001252e-16
-11,2048,1015,3.674838211509268e-14,,113.829809811,8.659776e6,8.881784197001252e-16
-12,4096,2039,5.007105841059456e-14,,226.551648901,1.7271872e7,1.7763568394002505e-15
-13,8192,3504,0.15776142489819278,,284.395517485,1.1173200968e10,56.555829106136216
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