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@Gkreindler
Gkreindler committed Dec 23, 2023
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Showing 7 changed files with 10,563 additions and 10,558 deletions.
1,000 changes: 500 additions & 500 deletions examples/temp/fits_boot.csv
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20,000 changes: 10,000 additions & 10,000 deletions examples/temp/fits_boot_all.csv
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4 changes: 2 additions & 2 deletions examples/temp/step1/Wstep2.csv
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@@ -1,2 +1,2 @@
0.7160381402040145,-0.043487516296841375
-0.043487516296841375,0.0027167729488170337
0.7160381402040097,-0.04348751629684115
-0.04348751629684115,0.002716772948817025
40 changes: 20 additions & 20 deletions examples/temp/step1/results.csv
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Original file line number Diff line number Diff line change
@@ -1,21 +1,21 @@
idx,obj_value,converged,iterations,iteration_limit_reached,time_it_took,theta_hat,theta0,is_optimum
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40 changes: 20 additions & 20 deletions examples/temp/step2/results.csv
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@@ -1,21 +1,21 @@
idx,obj_value,converged,iterations,iteration_limit_reached,time_it_took,theta_hat,theta0,is_optimum
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35 changes: 20 additions & 15 deletions src/functions_estimation.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -86,6 +86,9 @@ Base.@kwdef mutable struct GMMOptions
optim_autodiff::Symbol = :none
optim_algo = LBFGS()
optim_opts = nothing
optim_algo_bounds::Bool = false
lower_bound = nothing
upper_bound = nothing
write_iter::Bool = false # write to file each result (each initial run)
clean_iter::Bool = false #
overwrite::Bool = false
Expand Down Expand Up @@ -418,23 +421,25 @@ function fit_onerun(
# load the data
gmm_objective_loaded = theta -> gmm_objective(theta, data, mom_fn, W, weights, trace=opts.trace)

# optimize
if opts.optim_autodiff == :forward
(opts.trace > 0) && print("using AD")
time_it_took = @elapsed raw_opt_results = Optim.optimize(gmm_objective_loaded,
theta0,
opts.optim_algo, # defalut = LBFGS()
opts.optim_opts,
autodiff=:forward)

# results = optimize(f, g!, lower, upper, initial_x, Fminbox(GradientDescent()), Optim.Options(outer_iterations = 2))

# Optim.jl optimize
optim_main_args = []
push!(optim_main_args, gmm_objective_loaded)
if opts.optim_algo_bounds
push!(optim_main_args, opts.lower_bound)
push!(optim_main_args, opts.upper_bound)
end
push!(optim_main_args, theta0)

push!(optim_main_args, opts.optim_algo) # defalut = LBFGS()
push!(optim_main_args, opts.optim_opts)
if opts.optim_autodiff != :none
kwargs = (autodiff = :forward, )
else
time_it_took = @elapsed raw_opt_results = Optim.optimize(gmm_objective_loaded,
theta0,
opts.optim_algo, # defalut = LBFGS()
opts.optim_opts)
kwargs = ()
end

time_it_took = @elapsed raw_opt_results = Optim.optimize(optim_main_args...; kwargs...)

#=
summary(res)
minimizer(res)
Expand Down
2 changes: 1 addition & 1 deletion src/functions_regtable.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -44,7 +44,7 @@ has_fe(m::GMMModel) = false
# RegressionTables.get_coefname(x::Tuple{Vararg{Term}}) = RegressionTables.get_coefname.(x)
# RegressionTables.replace_name(x::Tuple{Vararg{Any}}, a::Dict{String, String}, b::Dict{String, String}) = [RegressionTables.replace_name(x[i], a, b) for i=1:length(x)]

RegressionTables.formula(m::GMMModel) = term(m.responsename) ~ sum(term.(String.(m.coefnames)))
# RegressionTables.formula(m::GMMModel) = term(m.responsename) ~ sum(term.(String.(m.coefnames)))

StatsAPI.coef(m::GMMModel) = m.coef
StatsAPI.coefnames(m::GMMModel) = m.coefnames
Expand Down

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