hpdparameter: Highest Posterior Density (HPD) for a parameter

In QAEnsemble: Ensemble Quadratic and Affine Invariant Markov Chain Monte Carlo

Highest Posterior Density (HPD) for a parameter

Description

This function returns the upper and lower bound of the Highest Posterior Density (HPD) for a parameter based on the Chen-Shao Highest Posterior Density (HPD) Estimation Algorithm found in the book by Chen, Shao, and Ibrahim (2000). (The smallest 95% credible interval will be given by the HPD using alpha = 0.05)

Usage

hpdparameter(parameter_MCMC, alpha = 0.05)

Arguments

parameter_MCMC	a vector of the parameter samples for a single estimated parameter
alpha	100(1 - alpha)% credible interval with the default value as alpha = 0.05

Value

A vector is returned that contains the lower and upper bound of the Highest Posterior Density (HPD) for a parameter (this will be the smallest 95% credible interval using alpha = 0.05)

References

Chen M, Shao Q, Ibrahim JG (2000) Monte Carlo Methods in Bayesian Computation. New York-New York: Springer-Verlag.

Examples

x_parameter = rnorm(75, mean = 0, sd = 1)

hpdparameter(x_parameter, 0.05)

QAEnsemble documentation built on April 3, 2025, 11:04 p.m.