pymc.compute_log_prior#
- pymc.compute_log_prior(idata, var_names=None, extend_inferencedata=True, model=None, sample_dims=('chain', 'draw'), progressbar=True)[source]#
Compute elemwise log_prior 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_prior. Defaults to all all free 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
- idata
- Returns:
- idata
InferenceData InferenceData with log_prior group
- idata