plotCumu: Plot MCMC Cumulative Quantiles

In plotMCMC: MCMC Diagnostic Plots

Description

Plot Markov chain Monte Carlo cumulative quantiles. This is a diagnostic plot for deciding whether the chain has converged.

Usage

plotCumu(mcmc, probs=c(0.025,0.975), div=1, log=FALSE, base=10,
         main=NULL, xlab="Iterations", ylab="Value", lty.median=1,
         lwd.median=2, col.median="black", lty.outer=2, lwd.outer=1,
         col.outer="black", ...)

Arguments

mcmc	MCMC chain(s) as a vector, data frame or mcmc object.
probs	vector of outer quantiles to draw, besides the median.
div	denominator to shorten values on the y axis.
log	whether values should be log-transformed.
base	logarithm base.
main	main title.
xlab	x-axis label.
ylab	y-axis label.
lty.median	line type of median.
lwd.median	line width of median.
col.median	color of median.
lty.outer	line type of outer quantiles.
lwd.outer	line width of outer quantiles.
col.outer	color of outer quantiles.
...	passed to cumuplot, 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

cumuplot is the underlying plotting function, and quantile is called iteratively to calculate the cumulative quantiles.

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

plotDens and plotQuant are posterior plots.

plotMCMC-package gives an overview of the package.

Examples

plotCumu(xpar$R0, main="R0")
plotCumu(xpar$cSfull, main="cSfull")
plotCumu(xpar, probs=c(0.25,0.75), ann=FALSE, axes=FALSE)

Example output

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