credint: Calculate Bayesian credible intervals

In bbolker/emdbook: Support Functions and Data for "Ecological Models and Data"

Calculate Bayesian credible intervals

Description

Calculate Bayesian credible intervals based on various types of information about the posterior distribution

Usage

tcredint(dist, parlist, ranges, level = 0.95, eps = 1e-05,verbose=FALSE)
ncredint(pvec,npost,level=0.95,tol=0.01,verbose=FALSE)

Arguments

dist	character string giving the name of a distribution for which "d", "q", and "p" function exist, e.g. "beta"
parlist	list of parameters to pass to distribution functions
ranges	lower, middle, and upper values to bracket lower and upper boundaries of the credible interval
level	confidence level
eps	if ranges is missing, set lower and upper brackets to the eps and 1-eps quantiles of the distribution
tol	tolerance on credible interval
verbose	if TRUE, return detailed information on the probability cutoff and realized area of the credible interval; if FALSE, just lower and upper bounds of the credible region
pvec	numeric vector of parameter values
npost	numeric vector of posterior density values corresponding to pvec

Details

tcredint gives credible intervals for a theoretical posterior density with defined density, cumulative density, and quantile functions; ncredint gives credible intervals for a numerical posterior density.

Value

A numeric vector giving the credible interval. If verbose=FALSE, gives just lower and upper bounds; if verbose=TRUE, also gives information on the probability cutoff and realized area of the credible interval

Note

For credible intervals from a sample (e.g. from an MCMC run), see HPDinterval in the coda package.

Author(s)

Ben Bolker

Examples

tcredint("beta",list(shape1=5,shape2=10),verbose=TRUE)
pvec = seq(0,1,length=100)
postvec = dbeta(pvec,shape1=5,shape2=10)
ncredint(pvec,postvec,verbose=TRUE)
set.seed(1001)

bbolker/emdbook documentation built on July 4, 2023, 1:16 p.m.