Computing Highest Posterior Density (HPD) Intervals
Compute approximate HPD intervals out of MCMC-samples in BayesX
hpd(data, alpha = 0.05, ...) hpd.coda(data, alpha = 0.05)
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 content of the intervals.. The default is alpha = 0.05. |
... |
Further parameters to be passed to the internal call of |
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.
Nadja Klein
res <- read.table(system.file("examples/nonparametric_f_x_pspline_sample.raw",
package="BayesX"), header = TRUE)
hpd(res)
hpd.coda(res)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.