hpd.coda

Compute approximate HPD intervals out of MCMC-samples in BayesX

MCMC

Functions for exploring and visualising estimation results
obtained with BayesX, a free software for estimating structured additive
regression models (<https://www.uni-goettingen.de/de/bayesx/550513.html>). In addition,
functions that allow to read, write and manipulate map objects that are required in spatial
analyses performed with BayesX.

Nikolaus Umlauf

BayesX

R Utilities Accompanying the Software Package BayesX

Thomas Kneib

Nadja Klein

Felix Heinzl

Andreas Brezger

Daniel Sabanes Bove

hpd function

<dl> <dt>data</dt>
<dd>Either the name of a file or a data frame containing the sample.</dd> <dt>alpha</dt>
<dd>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.</dd> <dt>...</dt>
<dd>Further parameters to be passed to the internal call of <code>optim</code>
 and <code>integrate</code>.</dd></dl>

Arguments

Author

Computing Highest Posterior Density (HPD) Intervals — hpd

<dl>

 <dt>data</dt>
<dd>Either the name of a file or a data frame containing the sample.</dd>

 <dt>alpha</dt>
<dd>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.</dd>

 <dt>...</dt>
<dd>Further parameters to be passed to the internal call of <code>optim</code>
 and <code>integrate</code>.</dd>

</dl>

hpd: Computing Highest Posterior Density (HPD) Intervals

Description

Usage

Arguments

Author

Details

Examples