gen_control

Set computational options for the sampling algorithms used for a 'gen' model component

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

gen_control function

<dl><dt>MHprop</dt>
<dd>MH proposal for the variance component in case of a MLiG prior
on the coefficients. The two options are "GiG" for a generalized inverse gamma
proposal, and "LNRW" for a log-normal random walk proposal. The former should
approximate the conditional posterior quite well provided MLiG parameter <code>a</code>
is large, such that the coefficients' prior is approximately normal.</dd></dl>

Arguments

Set computational options for the sampling algorithms used for a 'gen' model component — gen_control

<dl>

<dt>MHprop</dt>
<dd>MH proposal for the variance component in case of a MLiG prior
on the coefficients. The two options are "GiG" for a generalized inverse gamma
proposal, and "LNRW" for a log-normal random walk proposal. The former should
approximate the conditional posterior quite well provided MLiG parameter <code>a</code>
is large, such that the coefficients' prior is approximately normal.</dd>

</dl>

gen_control: Set computational options for the sampling algorithms used for a 'gen' model component

Description

Usage

Value

Arguments