bebi103.hmc.tau_hat

bebi103.hmc.tau_hat(samples, omit=(), omit_array_entry=())

Compute the empirical integrated autocorrelation time for each expectand for each chain.

Parameters:

• samples (cmdstanpy.CmdStanMCMC instance or dict) – MCMC samples from which to compute tau_hat, either as a cmdstanpy.CmdStanMCMC instance or as a dictionary of two-dimensional arrays for each expectand. For the dictionary, the first dimension of each element indexes the Markov chains and the second dimension indexes the sequential states within each Markov chain.

• omit (str, re.Pattern, or iterable thereof) – Glob pattern(s) matched against the base (non-indexed) name of each variable. Any variable whose base name matches an entry is omitted, whether scalar or array valued. For example, omit=’*_pred’ omits every variable whose name ends in ‘_pred’. Compiled re.Pattern entries are matched as regular expressions. A single string or pattern may be given instead of an iterable.

• omit_array_entry (str or iterable of str) – Specific array entries to omit, e.g. ‘y_pred[1]’ or ‘beta[1,2]’. Each entry must include bracketed, comma-separated integer indices. A single string may be given instead of an iterable.