plotAuto: Plot MCMC Autocorrelation

In plotMCMC: MCMC Diagnostic Plots

Description

Plot Markov chain Monte Carlo autocorrelation over a range of lag values. This is a diagnostic plot for deciding whether a chain needs further thinning.

Usage

plotAuto(mcmc, thin=1, log=FALSE, base=10, main=NULL, xlab="Lag",
         ylab="Autocorrelation", lty=1, lwd=1, col="black", ...)

Arguments

mcmc	MCMC chain(s) as a vector, data frame or mcmc object.
thin	interval to subsample chain(s), or 1 to keep chain intact.
log	whether values should be log-transformed.
base	logarithm base.
main	main title.
xlab	x-axis label.
ylab	y-axis label.
lty	line type.
lwd	line width.
col	line color.
...	passed to autocorr.plot, title, and axis.

Value

Null, but a plot is drawn on the current graphics device.

Note

The Args function from the gdata package is recommended for reviewing the arguments, instead of args.

See Also

autocorr.plot is the underlying plotting function, and window.mcmc is used to optionally thin the chain(s).

plotTrace, plotAuto, plotCumu, and plotSplom are diagnostic plots.

plotDens and plotQuant are posterior plots.

plotMCMC-package gives an overview of the package.

Examples

plotAuto(xpar$R0)
plotAuto(xpar$R0, thin=10)
plotAuto(xpar, lag.max=50, ann=FALSE, axes=FALSE)

Example output

plotMCMC documentation built on Nov. 23, 2020, 5:08 p.m.