factorizing posterior samplers + inclusion of slice sampler
I am going to make a pull request from by personal branch https://github.com/rattoma/dynare/tree/slice
the aim is to add a new posterior sampler, SLICE, but also to make it easier to add further new ones. There is a bunch of common codes in random walk, independent, TARB, etc. and I did not want to follow that route.
So I wrote, adapting from random walk algorithm, a new general set of routines
that factorizes the iteration of individual samplers, but the rest of the engine is common: initialization, parallelization, bars,
The current implementation fully integrates:
- random walk MH
- independent MH
It also contains a quick fix for TARB but the latter could be easily fully integrated in the new framework.
An open issue concerns adaptive_metropolis_hastings.m [last commit in 2013], which cannot be easily integrated, so I trapped it in dynare_estimation_1.m keeping the old framework.
Concerning pre-processor provisions, this commit would require:
- enable slice as new sampler method:
options_.posterior_sampling_method = 'slice';
- enable a form of flexible method specific options, along the lines of optimizers options. would this be possible? To explain better:
I added a new option field
options_.posterior_sampler_optionsthat can contain method specific options. one could specify a syntax like
sampler_options=(NAME, VALUE, etc..)
with name/value pairs. These will be stored as fields of
So the command
estimation(posterior_sampling_method = slice, sampler_options=('rotated',1), ...)
options_.posterior_sampler_options.rotated = 1
what do you think?