negbinomial_control: Set computational options for the sampling algorithms

In mcmcsae: Markov Chain Monte Carlo Small Area Estimation

Set computational options for the sampling algorithms

Description

Set computational options for the sampling algorithms

Usage

negbinomial_control(PG.approx = TRUE, PG.approx.m = -2L, CRT.approx.m = 20L)

Arguments

PG.approx	whether Polya-Gamma draws for logistic binomial models are approximated by a hybrid gamma convolution approach. If not, BayesLogit::rpg is used, which is exact for some values of the shape parameter.
PG.approx.m	if PG.approx=TRUE, the number of explicit gamma draws in the sum-of-gammas representation of the Polya-Gamma distribution. The remainder (infinite) convolution is approximated by a single moment-matching gamma draw. Special values are: -2L for a default choice depending on the value of the shape parameter balancing performance and accuracy, -1L for a moment-matching normal approximation, and 0L for a moment-matching gamma approximation.
CRT.approx.m	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.

Value

A list with computational options for the sampling algorithm.

mcmcsae documentation built on July 21, 2026, 1:06 a.m.