plot.bmk: Plot Hellinger Distances
In LaplacesDemon: Complete Environment for Bayesian Inference

Description Usage Arguments Details See Also Examples

This function plots Hellinger distances in an object of class bmk.

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## S3 method for class 'bmk'
plot(x, col=colorRampPalette(c("black","red"))(100),
     title="", PDF=FALSE, Parms=NULL, ...)

`x`	This required argument is an object of class `bmk`. See the `BMK.Diagnostic` function for more information.
`col`	This argument specifies the colors of the cells. By default, the `colorRampPalette` function colors large Hellinger distances as `red`, small as `black`, and provides 100 color gradations.
`title`	This argument specifies the title of the plot, and the default does not include a title.
`PDF`	Logical. When `TRUE`, the plot is saved as a .pdf file.
`Parms`	This argument accepts a vector of quoted strings to be matched for selecting parameters for plotting. This argument defaults to `NULL` and selects every parameter for plotting. Each quoted string is matched to one or more parameter names with the `grep` function. For example, if the user specifies `Parms=c("eta", "tau")`, and if the parameter names are beta[1], beta[2], eta[1], eta[2], and tau, then all parameters will be selected, because the string `eta` is within `beta`. Since `grep` is used, string matching uses regular expressions, so beware of meta-characters, though these are acceptable: ".", "[", and "]".
`...`	Additional arguments are unused.

The plot.bmk function plots the Hellinger distances in an object of class bmk. This is useful for quickly finding portions of chains with large Hellinger distances, which indicates non-stationarity and non-convergence.

BMK.Diagnostic

library(LaplacesDemon)
N <- 1000 #Number of posterior samples
J <- 10 #Number of parameters
Theta <- matrix(runif(N*J),N,J)
colnames(Theta) <- paste("beta[", 1:J, "]", sep="")
for (i in 2:N) {Theta[i,1] <- Theta[i-1,1] + rnorm(1)}
HD <- BMK.Diagnostic(Theta, batches=10)
plot(HD, title="Hellinger distance between batches")