Description Usage Arguments Details Value
View source: R/SimulateDiscreteDistributions.R
Simulates from the bivariate negative binomial distribution
1 | Bivariate_NBsim(N, kappa, p1, p2)
|
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 |
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.
An N\times 2 matrix with N simulated values from the bivariate negative binomial distribution
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