# zhusuan.diagnostics¶

effective_sample_size(samples, burn_in=100)

Compute the effective sample size of a chain of vector samples, using the algorithm in Stan. Users should flatten their samples as vectors if not so.

Parameters: samples – A 2-D numpy array of shape (M, D), where M is the number of samples, and D is the number of dimensions of each sample. burn_in – The number of discarded samples. A 1-D numpy array. The effective sample size.
effective_sample_size_1d(samples)

Compute the effective sample size of a chain of scalar samples.

Parameters: samples – A 1-D numpy array. The chain of samples. A float. The effective sample size.