# autocorr

From coda v0.17-1
by Martyn Plummer

##### Autocorrelation function for Markov chains

`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.

- Keywords
- ts

##### 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.

##### See Also

*Documentation reproduced from package coda, version 0.17-1, License: GPL (>= 2)*

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