rs: rejection sampling

In MarcoDVisser/MCMCR: Markov-chain monte-carlo methods and rejection sampling in R

Description

Protocol for a simple rejection sampling algorithm. Given a set of priors to sample N parameters from the algoritm accepts new proposal proportional to a random fraction. The sequence of parameters are randomly reversed.

Usage

rs(dat, start, LL, priors, N, giveup = 100)

Arguments

dat	dataset to be based to the likelihood function
start	a vector of starting values
LL	a likelihood function that accepts the parameters and data
priors	a function that randomly samples parameters from their prior distributions
N	total number of sampling rounds (one rounds goes through all parameters once).
giveup	after how many rounds of no new accepted values does the algorithm give up and assume convergence?

Author(s)

Marco D. Visser

MarcoDVisser/MCMCR documentation built on May 7, 2019, 2:49 p.m.