negbin_control

Set computational options for the sampling algorithms

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

negbin_control function

<dl><dt>CRT.approx.m</dt>
<dd>scalar integer specifying the degree of approximation to sampling
from a Chinese Restaurant Table distribution. The approximation is based on Le Cam's theorem.
Larger values yield a slower but more accurate sampler.</dd></dl>

Arguments

Set computational options for the sampling algorithms — negbin_control

<dl>

<dt>CRT.approx.m</dt>
<dd>scalar integer specifying the degree of approximation to sampling
from a Chinese Restaurant Table distribution. The approximation is based on Le Cam's theorem.
Larger values yield a slower but more accurate sampler.</dd>

</dl>

negbin_control: Set computational options for the sampling algorithms

Description

Usage

Value

Arguments