Bivariate_NBsim: Simulates from the bivariate negative binomial distribution

Description Usage Arguments Details Value Examples

View source: R/SimulateDiscreteDistributions.R

Description

Simulates from the bivariate negative binomial distribution

Usage

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Bivariate_NBsim(N, kappa, p1, p2)

Arguments

N

number of data points to be simulated

kappa

parameter κ of the bivariate negative binomial distribution

p1

parameter p_1 of the bivariate negative binomial distribution

p2

parameter p_2 of the bivariate negative binomial distribution

Details

A random vector {\bf X}=(X_1,X_2)' is said to follow the bivariate negative binomial distribution with parameters κ, p_1, p_2 if its probability mass function is given by

P({\bf X}={\bf x})=\frac{Γ(x_1+x_2+κ)}{x_1!x_2! Γ(κ)}p_1^{x_1}p_2^{x_2}(1-p_1-p_2)^{κ},

where, for i=1,2, x_i\in\{0,1,…\}, 0<p_i<1 such that p_1+p_2<1 and κ>0.

Value

An N\times 2 matrix with N simulated values from the bivariate negative binomial distribution

Examples

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set.seed(1)
kappa <- 3
p1 <- 0.1
p2 <- 0.85
N <- 100
#Simulate N realisations from the bivariate negative binomial distribution
y <- Bivariate_NBsim(N,kappa,p1,p2)

trawl documentation built on Aug. 16, 2018, 5:04 p.m.