pymc.model.core.Model.compile_logp

Model.compile_logp(vars=None, jacobian=True, sum=True, **compile_kwargs)

Compiled log probability density function.

Parameters:

varslist of random variables or potential terms, optional

Compute the gradient with respect to those variables. If None, use all free and observed random variables, as well as potential terms in model.

jacobianbool

Whether to include jacobian terms in logprob graph. Defaults to True.

sumbool

Whether to sum all logp terms or return elemwise logp for each variable. Defaults to True.