pymc.model.core.Model.logp#
- Model.logp(vars=None, jacobian=True, sum=True)[source]#
Elemwise log-probability of the model.
- Parameters:
- vars
list
ofrandom
variables
orpotential
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.
- vars
- Returns:
Logp
graph
(s
)