hpdparameter {QAEnsemble} | R Documentation |
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)