gammamixdpareto_fit: Fits the gamma mixture discrete Pareto distribution (GMDP) to...

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

Description

This function computes the estimates of parameter in GMDP model.

Usage

gammamixdpareto_fit(data, delta = 1, p = 0.5, method = "MLE")

Arguments

data	bivariate vector (X,N) observations from GMDP model.
delta	initial guess of true parameter δ which is numeric and must be greater than 0 (Default value is 1).
p	initial guess of true parameter p which must be numeric value between 0 and 1 (Default value is 0.5).
method	method of estimation for discrete Pareto parameter: EM=EM algorithm or MLE=maximum likelihood estimation (Default method is EM).

Details

bgammageo_fit GMDP model to data.

Value

vector of parameter estimates.

References

Amponsah, C. K., Kozubowski, T. J. and Panorska, A. K. (2019). A bivariate distribution with gamma mixture discrete Pareto marginals . In print. https://scholarworks.unr.edu/bitstream/handle/11714/2065/Amponsah_unr_0139M_12378.pdf?sequence=1&isAllowed=y

Examples

Data.df<- rgammamixdpareto(n=1000,alpha=1,beta=2,delta=0.45, p=0.8)
fit <- gammamixdpareto_fit(data = Data.df)
fit

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