dmgeo: The multivariate geometric distribution (MGEO)

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

Description

Probability mass function for multivariate geometric distribution with parameters $p_1,...,p_d$ in (0,1)$ and -1<θ < \dfrac{1-\min(p_1,...,p_d)}{1+\min(p_1,...,p_d)}.

Usage

dmgeo(data, theta, prob, log.p = FALSE)

Arguments

data	is a data frame MGEO model.
theta	numeric parameter which must be greater than -1 but less than (1-min(p))/(1+min(p)).
prob	vector of parameters between 0 and 1.
log.p	logical; if TRUE, probabilities p are given as log(p).

Details

dmgeo is the probability mass function.

Value

vector of probabilities.

References

Kozubowski, T.J., & Panorska, A.K. (2005). A Mixed bivariate distribution with exponential and geometric marginals. Journal of Statistical Planning and Inference, 134, 501-520. https://doi.org/10.1016/j.jspi.2004.04.010

Examples

data<-rmgeo(n=20, theta = 2, prob = c(0.6, 0.1))
den<-dmgeo(data, theta=2, prob = c(0.6, 0.1))
den

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