arviz.PyStanSamplingWrapper#
- class arviz.PyStanSamplingWrapper(model, idata_orig=None, log_lik_fun=None, is_ufunc=True, posterior_vars=None, sample_kwargs=None, idata_kwargs=None, log_lik_kwargs=None, apply_ufunc_kwargs=None)[source]#
PyStan (3.0+) sampling wrapper base class.
See the documentation on
SamplingWrapper
for a more detailed description. An example ofPyStanSamplingWrapper
usage can be found in the Refitting PyStan (3.0+) models with ArviZ notebook.Warning
Sampling wrappers are an experimental feature in a very early stage. Please use them with caution.
Methods
PyStanSamplingWrapper.__init__
(model[, ...])Check that all methods listed are implemented.
Convert the fit object returned by
self.sample
to InferenceData.Retrieve the log likelihood of the excluded observations from
idata__i
.Rebuild and resample the PyStan model on modified_observed_data.
Select a subset of the observations in idata_orig.