A Generic Multivariate Distribution for Counting Data

2011/03/24 by Marcos A. Capistrán, Capistrán, Marcos, J. Andrés Christen +1 · 1 citation
Computer Science · Mathematics · #62E15 #62P10 #Applications (stat.AP) #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Statistical Methods and Bayesian Inference

paper · pdf · doi:10.48550/arxiv.1103.4866

openalex publication_date 2011/03/24 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28

Abstract

Motivated by the need, in some Bayesian likelihood free inference problems, of imputing a multivariate counting distribution based on its vector of means and variance-covariance matrix, we define a generic multivariate discrete distribution. Based on blending the Binomial, Poisson and Negative-Binomial distributions, and using a normal multivariate copula, the required distribution is defined. This distribution tends to the Multivariate Normal for large counts and has an approximate pmf version that is quite simple to evaluate.

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