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########## R-function: summChainsDensEst ##########
# Summarises chains for vertical slices of a density estimate.
# Last changed: 27 SEP 2020
summChainsDensEst <- function(xMat,parNames,colourVersion=TRUE,paletteNum=1)
{
# Define required functions:
empty.panel <- function()
{
plot(0,0,type="n",xlim=c(0,1),ylim=c(0,1),xaxt="n",
yaxt="n",xlab="",ylab="",bty="o")
invisible()
}
# Set dimension and other variables:
numPar <- ncol(xMat)
sampSize <- nrow(xMat)
if (colourVersion)
{
if (paletteNum==1)
columnCols <- c("purple4","tomato","mediumblue","olivedrab4")
if (paletteNum==2)
columnCols <- c("darkmagenta", "green4","darkorange","dodgerblue")
}
if (!colourVersion)
{
columnCols <- rep(NA,numPar)
for (i in 1:4)
columnCols[i] <- "black"
}
oldpar <- par(no.readonly = TRUE)
on.exit(par(oldpar))
par(mfrow=c((numPar+1),4))
par(ann=F,mar=rep(0,4),xaxt="n",yaxt="n",xpd=TRUE)
empty.panel()
text(0.5,0.85,"vertical slice",cex=2,col=columnCols[1])
text(0.5,0.5,"of log-density",cex=2,col=columnCols[1])
text(0.5,0.15,"function",cex=2,col=columnCols[1])
par(ann=F,mar=rep(0,4),xaxt="n",yaxt="n",xpd=TRUE)
empty.panel()
text(0.5,0.5,"trace",cex=2.9,col=columnCols[2])
par(ann=F,mar=rep(0,4),xaxt="n",yaxt="n",xpd=TRUE)
empty.panel()
text(0.5,0.5,"lag 1",cex=2.9,col=columnCols[3])
par(ann=F,mar=rep(0,4),xaxt="n",yaxt="n",xpd=TRUE)
empty.panel()
text(0.5,0.5,"acf",cex=2.9,col=columnCols[4])
for (j in 1:numPar)
{
# Write the variable name:
par(ann=F,mar=c(0,0,0,0),xaxt="n",yaxt="n")
empty.panel()
if (length(parNames[[j]])==1)
text(0.5,0.5,parNames[[j]][1],cex=3.0,col=columnCols[1])
if (length(parNames[[j]])==2)
{
text(0.5,0.7,parNames[[j]][1],cex=1.9,col=columnCols[1])
text(0.5,0.3,parNames[[j]][2],cex=1.9,col=columnCols[1])
}
if (length(parNames[[j]])==3)
{
text(0.5,0.8,parNames[[j]][1],cex=1.55,col=columnCols[1])
text(0.5,0.5,parNames[[j]][2],cex=1.55,col=columnCols[1])
text(0.5,0.2,parNames[[j]][3],cex=1.55,col=columnCols[1])
}
# Do the trace plot:
plot(xMat[,j],xlab="",ylab="",type="l",col=columnCols[2])
# Do the lag 1 plot:
plot(xMat[1:(sampSize-1),j],
xMat[2:sampSize,j],xlab="",ylab="",type="n")
points(xMat[1:(sampSize-1),j],
xMat[2:sampSize,j],pch=1,cex=0.5,col=columnCols[3])
# Do the autocorrelation function plot:
ci.col.val <- "black"
if (colourVersion) ci.col.val <- "blue"
acf(xMat[,j],lag.max=20,col=columnCols[4],
lwd=2,ci.col=ci.col.val)
}
invisible()
}
########## End of summChainsDensEst ##########
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