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pymc.compute_log_likelihood — PyMC 5.25.1 documentation

pymc.compute_log_likelihood(idata, *, var_names=None, extend_inferencedata=True, model=None, sample_dims=('chain', 'draw'), progressbar=True, compile_kwargs=None)[source]#

Compute elemwise log_likelihood of model given InferenceData with posterior group.

Parameters:

idataInferenceData

InferenceData with posterior group

var_namessequence of str, optional

List of Observed variable names for which to compute log_likelihood. Defaults to all observed variables.

extend_inferencedatabool, default True

Whether to extend the original InferenceData or return a new one

modelModel, optional

sample_dimssequence of str, default (“chain”, “draw”)

progressbarbool, default True

compile_kwargsdict[str, Any] | None

Extra compilation arguments to supply to compute_log_density()

Returns:

idataInferenceData

InferenceData with log_likelihood group

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