Afrika Statistika

Décomposition d'une loi de poisson pondérée en une combinaison convexe de lois duales

Dominique Mizere, Gélin Chedly Louzayadio, Rufin Bidounga, and Gabriel Kissita

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The probability distribution of a set of observation is most often defined as a convex combination of probability laws. To highlight this mixture of the laws, MCMC (Monte Carlo Markov Chain) which is an algorithm that generates a stationary Markov chain is often used; laws being considered as normal laws. In this paper, the observations are positive integer, so it is assumed that the mixture law is a Poisson weighted law and Blending laws are dual. The purpose of this work is to determine the dual laws by simple algebraic properties. (Paper in French)

Article information

Afr. Stat., Volume 8, Number 1 (2013), 583-594.

First available in Project Euclid: 5 January 2014

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Digital Object Identifier

Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

Primary: 62F10: Point estimation
Secondary: 62H30: Classification and discrimination; cluster analysis [See also 68T10, 91C20]

Count Data Exponetial Family Weighted Poisson Distribution Fisher Index Overdispersion Underdispersion Dual Distribution Convex Combination


Mizere, Dominique; Louzayadio, Gélin Chedly; Bidounga, Rufin; Kissita, Gabriel. Décomposition d'une loi de poisson pondérée en une combinaison convexe de lois duales. Afr. Stat. 8 (2013), no. 1, 583--594. doi:10.4314/afst.v8i1.7.

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