Many thanks for the Julia version of Dynare, it is a pleasure to be using Dynare from Julia!
I am interested in running some Monte Carlo experiments, and I would like to access the estimated parameters in Julia, after doing maximum posterior or MCMC.
Starting with maximum posterior, I can see the estimated parameters in the context.results structure, but I can’t find a way to pull out the estimated parameter vector, to use in Julia. Similarly, for MCMC, I don’t see a way to access the posterior quantiles or the raw chain.
Thanks!
Actually, studying the source code for the estimation function, I see it now, in part:
results = context.results.model_results[1]
julia> results.estimation.posterior_mode
7-element Vector{Float64}:
0.9923027290016925
1.88954160889908
0.9075452454187274
0.008870398634074989
0.6907623612618923
0.0200331318674717
0.33131850116134115
I don’t find the posterior quantiles or the raw chains, however. Perhaps they are not saved?
Sorry, currently there is no accessor functions to access the estimation results.
When the posterior mode is computed, the following fields are available in context.results.model_results[1].estimation
posterior_mode
posterior_mode_std
posterior_mode_covariance
By default, the optimization is done with transformed_parameters
set to true and the parameters whose prior takes its value on a subset of R are transformed so as take their value on R.
When transformed_parameters
is true, in addition, the following results are stored:
transformed_posterior_mode
transformed_posterior_mode_std
transformed_posterior_mode_covariance
Currently we only store the MCMC chains in <modname>/output/mcm_chain_N.jls
where N
starts at one and increase every time that you run estimation
or rwmc_compute!()
for the same model (actually with the same context
).
You can recover the chain with
using Serialization
C = deserialize("<modname>/output/mcm_chain_1.jls")
for example.
Please open another issue to request accessor functions for estimation results.