Abstract
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)
Citation
Dominique Mizere. Gélin Chedly Louzayadio. Rufin Bidounga. Gabriel Kissita. "Décomposition d'une loi de poisson pondérée en une combinaison convexe de lois duales." Afr. Stat. 8 (1) 583 - 594, November 2013. https://doi.org/10.4314/afst.v8i1.7
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