arviz.PyStan2SamplingWrapper#

class arviz.PyStan2SamplingWrapper(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 (2.x) sampling wrapper base class.

See the documentation on SamplingWrapper for a more detailed description. An example of PyStanSamplingWrapper usage can be found in the Refitting PyStan (3.0+) models with ArviZ notebook. For usage examples of other wrappers see the user guide pages on Sampling wrappers.

Warning

Sampling wrappers are an experimental feature in a very early stage. Please use them with caution.

See also

SamplingWrapper

Methods

PyStan2SamplingWrapper.__init__(model[, ...])

PyStan2SamplingWrapper.check_implemented_methods(methods)

Check that all methods listed are implemented.

PyStan2SamplingWrapper.get_inference_data(...)

Convert the fit object returned by self.sample to InferenceData.

PyStan2SamplingWrapper.log_likelihood__i(...)

Retrieve the log likelihood of the excluded observations from idata__i.

PyStan2SamplingWrapper.sample(...)

Resample the PyStan model stored in self.model on modified_observed_data.

PyStan2SamplingWrapper.sel_observations(idx)

Select a subset of the observations in idata_orig.