dpareto_fsa: Fisher Scoring algorithm (FSA) for estimation of discrete...

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

Description

This function computes MLE of discrete Pareto distribution using the FSA algorithm.

Usage

dpareto_fsa(
  N,
  delta = 1,
  p = NULL,
  lambda = NULL,
  maxiter = 20,
  tol = 1e-08,
  verb = FALSE
)

Arguments

N	vector of random sample from discrete Pareto distribution
delta	shape parameter which must be numeric greater than or equal to 0
p	numeric parameter between 0 and 1
lambda	learning parameter between 0 and 1
maxiter	maximum number of iterations
tol	tolerance value
verb	If TRUE, estimates are printed during each iteration.

Details

Takes initial guess for the parameters in discrete Pareto and the algorithm will estimate the MLE.

Value

list containg parameter estimates, Deviance and data frame of iteration

References

Amponsah, C. K., Kozubowski, T. J. and Panorska (2019). A computational approach to estimation of discrete Pareto parameters. Inprint.

Examples

N<-rdpareto(500, delta=0.2,p=0.6)
fit<-dpareto_em(N,maxiter = 1000)
fit$par

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