autocorrelation_plot¶

autocorrelation_plot(posteriors: dict[str, ndarray], max_lags: int = 30) → None

It plots the auto-correlation for each Markov chain for each regression variable.

The plot shows the auto-correlation trend from lag 0 (when auto-correlation is always 1) up to max_lags. The plot layout has number of rows equal to the number of regression variables and a number of columns equal to the number of chains.

Parameters¶

posteriorsdict: Posterior samples. Posteriors and relative samples are key-value pairs. Each sample is a numpy.ndarray with a number of rows equal to the number of iterations and a number of columns equal to the number of Markov chains.
max_lagsint, optional: Maximum number of lags to which compute the auto-correlation. The default is 30.

Raises

TypeError

If posteriors is not a dict,
if a posterior sample is not a numpy.ndarray,
if max_lags is not an int.

KeyError

If posteriors does not contain 'intercept' key.

ValueError

If a posterior sample is an empty numpy.ndarray,
if max_lags is less or equal to 0.