autocorr 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.
High autocorrelations within chains indicate slow mixing and, usually, slow convergence. It may be useful to thin out a chain with high autocorrelations before calculating summary statistics: a thinned chain may contain most of the information, but take up less space in memory. Re-running the MCMC sampler with a different parameterization may help to reduce autocorrelation.
autocorr(x, lags = c(0, 1, 5, 10, 50), relative=TRUE)A vector or array containing the autocorrelations.
an mcmc object
a vector of lags at which to calculate the autocorrelation
a logical flag. TRUE if lags are relative to the thinning interval of the chain, or FALSE if they are absolute difference in iteration numbers
Martyn Plummer
acf, autocorr.plot.