Implements Metropolis sampling for an arbitrary discrete probability distribution
random_walk(pd, start, num_steps)
Arguments
pd: function containing discrete probability function on the integers 1, 2, ...
start: starting value of algorithm
num_steps: number of iterations of algorithm
Returns
A vector of simulated values
Author(s)
Jim Albert
Examples
# random walk through a binomial distributionpd <-function(x){ dbinom(x, size =10, prob =0.5)}start <-4num_steps <-50out <- random_walk(pd, start, num_steps)