dfmbeg: The finite mixture of bivariate distribution with mixture...

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

Description

Density function for FMBEG model.

Usage

dfmbeg(data, beta, p, q, pi, log.p = FALSE)

Arguments

data	is bivariate vector (X,N) vector representing observations from FMBEG model.
beta	vector of parameters which must be numeric greater than 0.
p	vector of numeric parameters between 0 and 1 of the finite mixture of geometric distribution.
q	vector of gamma membership probabilities between 0 and 1, and sum equal to 1.
pi	vector of geometric membership probabilities between 0 and 1, and sum equal to 1.
log.p	logical; if TRUE, densities are given as logarithmic values.

Details

dfmbeg is the density function.

Value

vector of densities.

References

Amponsah, C. K. and Kozubowski, T.J., and Panorska, A.K. (2020). A finite mixture of bivariate distribution with mixture exponential and geometric (FMBEG) marginals. Inprint.

Examples

data.df <- rfmbeg(10, beta = c(1,2,10), p=0.5, q=c(0.3,0.2,0.5), pi=1)
den <- dfmbeg(data=data.df, beta = c(1,2,10), p=0.5, q=c(0.3,0.2,0.5), pi=1)
den

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