# R/plot.miss.R In LaplacesDemon: Complete Environment for Bayesian Inference

#### Documented in plot.miss

```###########################################################################
# plot.miss                                                               #
#                                                                         #
# The purpose of the plot.miss function is to plot an object of class     #
# miss.                                                                   #
###########################################################################

plot.miss <- function(x, PDF=FALSE, ...)
{
### Initial Checks
if(missing(x)) stop("The x argument is required.")
if(PDF == TRUE) {
pdf("MISS.Plots.pdf")
par(mfrow=c(3,3))
}
### Plot Imputations
for (i in 1:nrow(x\$Imp)) {
plot(1:ncol(x\$Imp), x\$Imp[i,], type="l", xlab="Iterations",
ylab="Value", main=paste("Imp[", i, ",]", sep=""))
panel.smooth(1:ncol(x\$Imp), x\$Imp[i,], pch="")
plot(density(x\$Imp[i,]), xlab="Value",
main=paste("Imp[", i, ",]"))
polygon(density(x\$Imp[i,]), col="black", border="black")
### Only plot an ACF if there's > 1 unique values
if(!is.constant(x\$Imp[i,])) {
z <- acf(x\$Imp[i,], plot=FALSE)
se <- 1/sqrt(length(x\$Imp[i,]))
plot(z\$lag, z\$acf, ylim=c(min(z\$acf,-2*se),1), type="h",
main=paste("Imp[", i, ",]"), xlab="Lag",
ylab="Correlation")
abline(h=(2*se), col="red", lty=2)
abline(h=(-2*se), col="red", lty=2)
}
else plot(0, 0, main=paste("Imp[", i, ",]"),
"is a constant.")}
if(PDF == TRUE) dev.off()
}

#End
```

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LaplacesDemon documentation built on July 1, 2018, 9:02 a.m.