BayesX (version 0.2-3)

hpd: Computing Highest Posterior Density (HPD) Intervals

Description

Compute approximate HPD intervals out of MCMC-samples in BayesX

Usage

hpd(data, alpha = 0.05, ...)
hpd.coda(data, alpha = 0.05, ...)

Arguments

data

Either the name of a file or a data frame containing the sample.

alpha

A numeric scalar in the interval (0,1) such that 1 - alpha is the target probability contained in the intervals.

...

Further parameters to be passed to the internal call of optim such has start and integrate such as lower.

Details

hpd computes the HPD interval based on a kernel density estimate of the samples. hpd.coda computes the HPD interval with the function HPDinterval available in package coda.

Examples

res <- read.table(system.file("examples/nonparametric_f_x_pspline_sample.raw",
                              package="BayesX"), header=TRUE)
hpd(res)
hpd.coda(res)