R: Autocorrelation function for Markov chains

autocorr {coda} | R Documentation

## Autocorrelation function for Markov chains

### Description

`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.

### Usage

    autocorr(x, lags = c(0, 1, 5, 10, 50), relative=TRUE)

### Arguments

`x` | an mcmc object
`lags` | a vector of lags at which to calculate the autocorrelation
`relative` | 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

### Value

A vector or array containing the autocorrelations.

### Author(s)

Martyn Plummer

### See Also

`acf`, `autocorr.plot`.

[Package coda version 0.19-1 Index]