# arviz.PyMCSamplingWrapper.log_likelihood__i#

PyMCSamplingWrapper.log_likelihood__i(excluded_obs, idata__i)#

Get the log likelilhood samples $$\log p_{post(-i)}(y_i)$$.

Calculate the log likelihood of the data contained in excluded_obs using the model fitted with this data excluded, the results of which are stored in idata__i.

Parameters:
excluded_obs

Observations for which to calculate their log likelihood. The second item from the tuple returned by sel_observations is passed as this argument.

idata__i: InferenceData

Inference results of refitting the data excluding some observations. The result of get_inference_data is used as this argument.

Returns:
log_likelihood: xr.Dataarray

Log likelihood of excluded_obs evaluated at each of the posterior samples stored in idata__i.