Autocorrelation function for Markov chains
autocorr calculates the autocorrelation function for the
mcmc.obj at the lags given by
The lag values are taken to be relative to the thinning interval
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)
- 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
- A vector or array containing the autocorrelations.