plotTrace: Plot MCMC Traces

In plotMCMC: MCMC Diagnostic Plots

Description

Plot Markov chain Monte Carlo traces. This is a diagnostic plot for deciding whether a chain shows unwanted trends.

Usage

plotTrace(mcmc, axes=FALSE, same.limits=FALSE,
          between=list(x=axes,y=axes), div=1, span=1/4, log=FALSE,
          base=10, main=NULL, xlab=NULL, ylab=NULL, cex.main=1.2,
          cex.lab=1, cex.axis=0.8, cex.strip=0.8, col.strip="gray95",
          las=0, tck=0.5, tick.number=5, lty.trace=1, lwd.trace=1,
          col.trace="gray", lty.median=1, lwd.median=1,
          col.median="black", lty.loess=2, lwd.loess=1,
          col.loess="black", plot=TRUE, ...)

Arguments

mcmc	MCMC chain(s) as a vector, data frame or mcmc object.
axes	whether axis values should be plotted.
same.limits	whether panels should have same x-axis limits.
between	list with x and y indicating panel spacing.
div	denominator to shorten values on the y axis.
span	smoothness parameter, passed to panel.loess
log	whether values should be log-transformed.
base	logarithm base.
main	main title.
xlab	x-axis title.
ylab	y-axis title.
cex.main	size of main title.
cex.lab	size of axis labels.
cex.axis	size of tick labels.
cex.strip	size of strip labels.
col.strip	color of strip labels.
las	orientation of tick labels: 0=parallel, 1=horizontal, 2=perpendicular, 3=vertical.
tck	tick mark length.
tick.number	number of tick marks.
lty.trace	line type of trace.
lwd.trace	line width of trace.
col.trace	color of trace.
lty.median	line type of median.
lwd.median	line width of median.
col.median	color of median.
lty.loess	line type of loess.
lwd.loess	line width of loess.
col.loess	color of loess.
plot	whether to draw plot.
...	passed to xyplot and panel.loess.

Value

When plot=TRUE, a trellis plot is drawn and a data frame is returned, containing the data used for plotting. When plot=FALSE, a trellis object is returned.

Note

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

See Also

xyplot and panel.loess are the underlying drawing functions, and traceplot is a similar non-trellis plot.

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

plotDens and plotQuant are posterior plots.

plotMCMC-package gives an overview of the package.

Examples

plotTrace(xpar, xlab="Iterations", ylab="Parameter value",
          layout=c(2,4))
plotTrace(xpar$R0, axes=TRUE, div=1000)

Example output

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