rCMP: Random number generator from CMP

In James-Thorson/Conway-Maxwell-Poisson: Conway-Maxwell-Poisson distribution

Usage

rCMP(n, lambda, mu, nu, tol = 0.01, x_max = 200)

Arguments

n
lambda
mu
nu
tol
x_max

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (n, lambda, mu, nu, tol = 0.01, x_max = 200) 
{
    loglike_x = rep(NA, x_max + 1)
    for (x in 0:x_max) {
        if (!missing(mu) & !missing(lambda)) 
            stop("'mu' and 'lambda' both specified")
        if (missing(mu) & !missing(lambda)) 
            loglike_x[x + 1] = dCMP(x = x, lambda = lambda, mu = mu, 
                nu = nu, log = TRUE, tol = tol, iter.max = x_max)
        if (!missing(mu) & missing(lambda)) 
            loglike_x[x + 1] = dCMP(x = x, lambda = lambda, mu = mu, 
                nu = nu, log = TRUE, tol = tol, iter.max = x_max)
        if (missing(mu) & missing(lambda)) 
            stop("Neither 'mu' or 'lambda' is specified")
    }
    n = sample(x = 0:x_max, size = n, replace = TRUE, prob = exp(loglike_x))
    return(n)
  }

James-Thorson/Conway-Maxwell-Poisson documentation built on May 7, 2019, 10:19 a.m.