pr_gig

Create an object representing Generalized Inverse Gaussian (GIG) prior distributions

Fit multi-level models with possibly correlated
random effects using Markov Chain Monte Carlo simulation.
Such models allow smoothing over space and time and are useful in,
for example, small area estimation.

Harm Jan Boonstra

mcmcsae

Markov Chain Monte Carlo Small Area Estimation

Grzegorz Baltissen

pr_gig function

<dl><dt>a</dt>
<dd>scalar or vector parameter.</dd>
<dt>b</dt>
<dd>scalar or vector parameter.</dd>
<dt>p</dt>
<dd>scalar or vector parameter.</dd></dl>

Arguments

Create an object representing Generalized Inverse Gaussian (GIG) prior distributions — pr_gig

<dl>

<dt>a</dt>
<dd>scalar or vector parameter.</dd>


<dt>b</dt>
<dd>scalar or vector parameter.</dd>


<dt>p</dt>
<dd>scalar or vector parameter.</dd>

</dl>

pr_gig: Create an object representing Generalized Inverse Gaussian (GIG) prior distributions

Description

Usage

Value

Arguments