[SOLVED] R, HPD (Highest posterior density) interval based on samples from posterior, WinBUGS

R, HPD (Highest posterior density) interval based on samples from posterior, WinBUGS

How to calculate HPD (Highest posterior density) interval from posterior samples? I have four parameters and i generate 1000 samples from posterior parameters distribution. Now How to calculate HPD in R software. I used package code But I got an error that

    HPDinterval(winbugsresult$sims.list,prob=0.05)
    Error in UseMethod("HPDinterval") : 
    no applicable method for 'HPDinterval' applied to an object of class "list"

where "winbugsresult" is a list that contains posterior samples.

I also used a vector I got following error

    HPDinterval(winbugsresult$sims.list$alpha ,prob=0.05)
    Error in UseMethod("HPDinterval") : 
    no applicable method for 'HPDinterval' applied to an object of class "c('double', 'numeric')"

I used just a random vector from normal and i got error again

    HPDinterval(rnorm(100))
    Error in UseMethod("HPDinterval") : 
    no applicable method for 'HPDinterval' applied to an object of class "c('double', 'numeric')"

Solution

I'm not quite sure what the structure of winbugsresult$sims.list (you could edit your answer to include str(winbugsresult$sims.list)), but converting a numeric vector or a matrix with as.mcmc() gives you an object you can pass to HPDinterval, e.g.

library(coda)
HPDinterval(as.mcmc(rnorm(1000)))
HPDinterval(as.mcmc(matrix(rnorm(1000),ncol=10)))  # matrix