dbgammageo: The bivariate gamma geometric distribution (BGG)

In camponsah/BivMixDist: Fit bivariate continous and discrete distributions as well as provide EM algorithm for discrete Pareto

Description

Density function for bivariate gamma geometric distribution with parameters α >0, β > 0 and p in (0,1).

Usage

dbgammageo(data, alpha, beta, p, log.p = FALSE)

Arguments

data	bivariate vector (X,N) observations from BGG model.
alpha	numeric parameter which must be greater than 0.
beta	numeric parameter which must be greater than 0.
p	numeric parameter between 0 and 1.
log.p	logical; if TRUE, probabilities p are given as log(p).

Details

dbgammageo is the density function for BGG model.

Value

vector of densities.

References

Barreto-Souza, W. (2012). Bivariate gamma-geometric law and its induced Lévy process . Journal of Multivariate Analysis, 109:130-145. https://doi.org/10.1016/j.jmva.2012.03.004

Examples

data.df<-rbgammageo(20, alpha=1.5, beta=2, p=0.6)
den<-dbgammageo(data.df, alpha=1.5, beta=2, p=0.6)
den

camponsah/BivMixDist documentation built on Nov. 15, 2021, 3:11 a.m.