pymc.compute_log_likelihood#
- 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:
- idata
InferenceData 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
- model
Model, optional - sample_dimssequence of
str, default (“chain”, “draw”) - progressbarbool, default
True - compile_kwargs
dict[str,Any] |None Extra compilation arguments to supply to
compute_log_density()
- idata
- Returns:
- idata
InferenceData InferenceData with log_likelihood group
- idata