Error Analysis on the Generalized Negative Binomial Distribution

On Hypergeometric Generalized Negative Binomial Distribution

The Negative Binomial Distribution Efficiency in Finite Mixture of Semi-parametric Generalized Linear Models

Introduction Selection the appropriate statistical model for the response variable is one of the most important problem in the finite mixture of generalized linear models. One of the distributions which it has a problem in a finite mixture of semi-parametric generalized statistical models, is the Poisson distribution. In this paper, to overcome over dispersion and computational burden, finite ...

Some Representations and Specifications of the Generalized Negative Binomial Distribution

Abstract: In a sequence of dependent Bernoulli trials, the distribution of the number of trials required to obtain r successes, Vr, is called a Generalized Negative Binomial (GNB) distribution. We present a simple representation of this distribution based on moments and consider the conditions under which a GNB distribution follows negative binomial distribution. Also we study the properties of...

Estimation in Misclassified Size-Biased Generalized Negative Binomial Distribution

In this paper, we are concerned with the situations, where sometimes value two is reported erroneously as one in relation to size biased generalized negative binomial distribution (SBGNBD) with probability αα. We have obtained the Maximum likelihood estimator and Bayes estimator under general entropy loss function. A simulated study is carried out to access the performance of the maximum likeli...

A Simple Method for Estimating Generalized Negative Binomial Distribution

A simple and quick method of estimating the parameters of the Generalized Negative Binomial Distribution (GNBD) has been suggested. A Monte Carlo technique has been applied to study the unbiasedness and the efficiency of the estimates so obtained. Using this method of estimation the GNBD has been fitted to some observed data and the fits have been found quite satisfactory.