HelpersMG (version 6.4)

rnbinom_new: Random numbers for the negative binomial distribution.

Description

See rnbinom.

Usage

rnbinom_new(n, size = NULL, prob = NULL, mu = NULL, sd = NULL, var = NULL)

Value

Random numbers for the negative binomial distribution

Arguments

n

number of observations.

size

target for number of successful trials, or dispersion parameter (the shape parameter of the gamma mixing distribution). Must be strictly positive, need not be integer.

prob

probability of success in each trial. 0 < prob <= 1.

mu

alternative parametrization via mean.

sd

alternative parametrization via standard deviation.

var

alternative parametrization via variance.

Author

Marc Girondot

Details

rnbinom_new returns random numbers for the negative binomial distribution

See Also

Other Distributions: cutter(), dSnbinom(), dbeta_new(), dcutter(), dggamma(), logLik.cutter(), plot.cutter(), print.cutter(), r2norm(), rcutter(), rmnorm()

Examples

if (FALSE) {
library("HelpersMG")
set.seed(1)
x <- rnbinom_new(n=1000, prob=6.25/(5+6.25), size=6.25)
mean(x)
sd(x)
set.seed(1)
x <- rnbinom_new(n=1000, mu=5, sd=3)
mean(x)
sd(x)
set.seed(1)
x <- rnbinom_new(n=1000, mu=5, var=3^2)
mean(x)
sd(x)
set.seed(1)
x <- rnbinom_new(n=1000, mu=5, size=6.25)
mean(x)
sd(x)
set.seed(1)
x <- rnbinom_new(n=1000, size=6.25, var=3^2)
mean(x)
sd(x)
set.seed(1)
x <- rnbinom_new(n=1000, prob=6.25/(5+6.25), var=3^2)
mean(x)
sd(x)
# Example of wrong parametrization
set.seed(1)
x <- rnbinom_new(n=1000, sd=3, var=3^2)
set.seed(1)
x <- rnbinom_new(n=1000, mu=10, var=3^2)
}