bayesR2

Compute a Bayesian measure of percentage of explained variance

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

bayesR2 function

<dl><dt>x</dt>
<dd>object of class mcdraws as created by <code>MCMCsim</code>.</dd>
<dt>summary</dt>
<dd>if <code>TRUE</code> only a posterior summary is returned, otherwise
a simulation (<code>dc</code>) object.</dd></dl>

Arguments

Compute a Bayesian measure of percentage of explained variance — bayesR2

<dl>

<dt>x</dt>
<dd>object of class mcdraws as created by <code>MCMCsim</code>.</dd>


<dt>summary</dt>
<dd>if <code>TRUE</code> only a posterior summary is returned, otherwise
a simulation (<code>dc</code>) object.</dd>

</dl>

bayesR2: Compute a Bayesian measure of percentage of explained variance

Description

Usage

Value

Arguments

References