pr_gig

Create an object containing information about 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>parameter of length 1 or <code>n</code>.</dd>
<dt>b</dt>
<dd>parameter of length 1 or <code>n</code>.</dd>
<dt>p</dt>
<dd>parameter of length 1 or <code>n</code>.</dd>
<dt>n</dt>
<dd>dimension, if known. For internal use only.</dd>
<dt>post</dt>
<dd>whether conditional posterior sampling function should be
created. For internal use only.</dd></dl>

Arguments

Create an object containing information about Generalized Inverse Gaussian (GIG) prior distributions — pr_gig

<dl>

<dt>a</dt>
<dd>parameter of length 1 or <code>n</code>.</dd>


<dt>b</dt>
<dd>parameter of length 1 or <code>n</code>.</dd>


<dt>p</dt>
<dd>parameter of length 1 or <code>n</code>.</dd>


<dt>n</dt>
<dd>dimension, if known. For internal use only.</dd>


<dt>post</dt>
<dd>whether conditional posterior sampling function should be
created. For internal use only.</dd>

</dl>

pr_gig: Create an object containing information about Generalized Inverse Gaussian (GIG) prior distributions

Description

Usage

Value

Arguments