random_walk: Metropolis sampling of a discrete distribution
In ProbBayes: Probability and Bayesian Modeling

Description Usage Arguments Value Author(s) Examples

Implements Metropolis sampling for an arbitrary discrete probability distribution

1	random_walk(pd, start, num_steps)

`pd`	function containing discrete probability function on the integers 1, 2, ...
`start`	starting value of algorithm
`num_steps`	number of iterations of algorithm

A vector of simulated values

Jim Albert

# random walk through a binomial distribution
pd <- function(x){
  dbinom(x, size = 10, prob = 0.5)
}
start <- 4
num_steps <- 50
out <- random_walk(pd, start, num_steps)