autplot1: Autocorrelation Plot of MCMC Output

In s-mckay-curtis/mcmcplots: Create Plots from MCMC Output

Description

Creates an autocorrelation or partial autocorrelation plot of MCMC output.

Usage

autplot1(x, chain = 1, lag.max = NULL, partial = FALSE,
col = mcmcplotsPalette(1), style = c("gray", "plain"),
ylim = NULL, ...)

Arguments

x	an mcmc.list object with a single variable.
chain	the number of the parallel chain for plotting. The default is to use the first parallel chain.
lag.max	passed as an argument to the autocorrelation function acf.
partial	logical indicating whether paritial autocorrelation should be plotted.
col	color of the bars in the plot.
style	if "gray", then the plotting region is printed with a gray background, otherwise the default plotting region is used.
ylim	limits for the y-axis.
...	further arguments passed to the plotting function.

Details

None.

Value

Creates a plot.

Author(s)

S. McKay Curtis (adapted from Martyn Plummer's autcorr.plot code in the coda package)

References

None.

See Also

acf, autocorr.plot

Examples

## Create fake MCMC output
nc <- 10; nr <- 1000
pnames <- c(paste("alpha[", 1:5, "]", sep=""), paste("gamma[", 1:5, "]", sep=""))
means <- rpois(10, 20)
fakemcmc <-
    coda::as.mcmc.list(
        lapply(1:3,
               function(i)
                   coda::mcmc(matrix(rnorm(nc*nr, rep(means,each=nr)),
                                     nrow=nr, dimnames=list(NULL,pnames)))))

autplot1(fakemcmc[, "alpha[1]", drop=FALSE])
autplot1(fakemcmc[, "alpha[1]", drop=FALSE], chain=2, style="plain")
autplot1(fakemcmc[, "alpha[1]", drop=FALSE], partial=TRUE)

s-mckay-curtis/mcmcplots documentation built on May 31, 2019, 5:13 p.m.