poisson_control: Set computational options for the sampling algorithms
In mcmcsae: Markov Chain Monte Carlo Small Area Estimation

poisson_control

R Documentation

Set computational options for the sampling algorithms

Set computational options for the sampling algorithms

poisson_control(nb.shape = 100, PG.approx = TRUE, PG.approx.m = -2L)

`nb.shape`	shape parameter of the negative binomial distribution used internally to approximate the Poisson distribution. This should be set to a relatively large value (default is 100), corresponding to negligible overdispersion, to obtain a good approximation to the Poisson sampling distribution. However, note that very large values may cause slow MCMC exploration of the posterior distribution.
`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.