Add to ORKGAbst ract. The present article shows that a limiting argument that is essentially the law of small numbers produces a proper discrete multivariate distribution from any generalized Poisson distribution. Based on this result, Engen's Extended Negative Binomial (ENB) model is derived from the Poisson-Pascal distribution, which is a generalization of the inverse Gaussian-Poisson distribution. The ENB model is also derived from Sichel's generalized inverse Gaussian-Poisson distribution. The application of the ENB model is discussed thereto. Key words and phrases: Compound Poisson, conditional inverse Gaussian Poisson, infinitely divisible, random clustering, species abundance. 1
The paper introduces the concept of a cluster structure to define a joint distribution of the sample...
Under a Poisson model, each infectious individual generates a number of secondary cases, drawn from ...
The Poisson distribution has been widely used for modelling rater agreement using loglinear models. ...
In a recent paper, Joe and Zhu [2005, Generalized Poisson distribution: the property of mixture of P...
Recent studies on biological data which vary somewhat from Poisson description have brought the nega...
During the past three decades or so there has been much work done concerning contagious probability ...
Motivated by the fundamental problem of measuring species diversity, this paper introduces the conce...
Consider two non-negative integer-valued r.v.'s X,Y with X=>Y. Suppose that the conditional distribu...
We study the convolution of compound negative binomial distributions with arbitrary parameters. The ...
<p>Motivated by the fundamental problem of modeling the frequency of frequencies (FoF) distribution,...
This thesis considers bivariate extension of the Meixner class of distributions by the method of gen...
extensively used for the description of data too heterogeneous to be fitted by a Poisson distributio...
Modeling empirical distributions of repeated counts with parametric probability distributions is a f...
The bivariate forms of many important discrete probability distributions have been studied by many s...
Two interesting results encountered in the literature concerning the Poisson and the negative binomi...
The paper introduces the concept of a cluster structure to define a joint distribution of the sample...
Under a Poisson model, each infectious individual generates a number of secondary cases, drawn from ...
The Poisson distribution has been widely used for modelling rater agreement using loglinear models. ...
In a recent paper, Joe and Zhu [2005, Generalized Poisson distribution: the property of mixture of P...
Recent studies on biological data which vary somewhat from Poisson description have brought the nega...
During the past three decades or so there has been much work done concerning contagious probability ...
Motivated by the fundamental problem of measuring species diversity, this paper introduces the conce...
Consider two non-negative integer-valued r.v.'s X,Y with X=>Y. Suppose that the conditional distribu...
We study the convolution of compound negative binomial distributions with arbitrary parameters. The ...
<p>Motivated by the fundamental problem of modeling the frequency of frequencies (FoF) distribution,...
This thesis considers bivariate extension of the Meixner class of distributions by the method of gen...
extensively used for the description of data too heterogeneous to be fitted by a Poisson distributio...
Modeling empirical distributions of repeated counts with parametric probability distributions is a f...
The bivariate forms of many important discrete probability distributions have been studied by many s...
Two interesting results encountered in the literature concerning the Poisson and the negative binomi...
The paper introduces the concept of a cluster structure to define a joint distribution of the sample...
Under a Poisson model, each infectious individual generates a number of secondary cases, drawn from ...
The Poisson distribution has been widely used for modelling rater agreement using loglinear models. ...