autocorr.diag: Autocorrelation function for Markov chains

In coda: Output Analysis and Diagnostics for MCMC

Autocorrelation function for Markov chains

Description

autocorr.diag calculates the autocorrelation function for the Markov chain mcmc.obj at the lags given by lags. The lag values are taken to be relative to the thinning interval if relative=TRUE. Unlike autocorr, if mcmc.obj has many parmeters it only computes the autocorrelations with itself and not the cross correlations. In cases where autocorr would return a matrix, this function returns the diagonal of the matrix. Hence it is more useful for chains with many parameters, but may not be as helpful at spotting parameters.

If mcmc.obj is of class mcmc.list then the returned vector is the average autocorrelation across all chains.

Usage

autocorr.diag(mcmc.obj, ...)

Arguments

mcmc.obj	an object of class mcmc or mcmc.list
...	optional arguments to be passed to autocorr

Value

A vector containing the autocorrelations.

Author(s)

Russell Almond

See Also

autocorr, acf, autocorr.plot.

coda documentation built on May 29, 2024, 11:23 a.m.