plotAuto {plotMCMC} | R Documentation |
Plot MCMC Autocorrelation
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 |
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 |
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)