In BlackEdder/mcmcsample: Work with posterior samples

The mcmcsample package extends ggplot2 to make it easier to plot the correlation between the parameters in your mcmc samples.

library(data.table)
param1 <- rnorm( 1000, 0, 1 )
param2 <- sapply(param1, function(x) x^2 + rnorm( 1, 0, 1 ) )
# Make sure to add a sample.id column
samples <- data.table( data.frame( list("sample.id"=seq(1,length(param1)), "param1"=param1, "param2"=param2) ) )

library(mcmcsample)
library(ggplot2)
long.samples <- melt(samples,measure.vars=c("param1","param2"),id.vars = c("sample.id"))
ggs <- gg.correlation(long.samples, "value", "variable")

Points that fall outside the credibility interval

library(mcmcsample)
library(ggplot2)
smpls <- samples
smpls$ci <- inside.ci(smpls[,.(param1,param2)],0.8, method="bin")
long.samples <- melt(smpls,measure.vars=c("param1","param2"),id.vars = c("sample.id","ci"))
ggs <- gg.correlation(long.samples, "value", "variable", colour="ci")