pr_normal

Create an object representing a possibly multivariate normal prior distribution

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_normal function

<dl><dt>mean</dt>
<dd>scalar or vector mean parameter.</dd>
<dt>precision</dt>
<dd>scalar, vector or matrix precision parameter.</dd>
<dt>labels</dt>
<dd>optional character vector with coefficient labels. If specified,
it should have the same size of at least one of <code>mean</code> and <code>precision</code>,
and in that case the normal prior with these parameters is assigned to these coefficients,
while any coefficients not present in labels will be assigned a non-informative
prior with mean 0 and precision 0.</dd></dl>

Arguments

Create an object representing a possibly multivariate normal prior distribution — pr_normal

<dl>

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


<dt>precision</dt>
<dd>scalar, vector or matrix precision parameter.</dd>


<dt>labels</dt>
<dd>optional character vector with coefficient labels. If specified,
it should have the same size of at least one of <code>mean</code> and <code>precision</code>,
and in that case the normal prior with these parameters is assigned to these coefficients,
while any coefficients not present in labels will be assigned a non-informative
prior with mean 0 and precision 0.</dd>

</dl>

pr_normal: Create an object representing a possibly multivariate normal prior distribution

Description

Usage

Value

Arguments