Please use this identifier to cite or link to this item:
Type: Artigo de periódico
Title: Multivariate models for correlated count data
Author: Rodrigues-Motta, M
Pinheiro, HP
Martins, EG
Araujo, MS
dos Reis, SF
Abstract: In this study, we deal with the problem of overdispersion beyond extra zeros for a collection of counts that can be correlated. Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial distributions have been considered. First, we propose a multivariate count model in which all counts follow the same distribution and are correlated. Then we extend this model in a sense that correlated counts may follow different distributions. To accommodate correlation among counts, we have considered correlated random effects for each individual in the mean structure, thus inducing dependency among common observations to an individual. The method is applied to real data to investigate variation in food resources use in a species of marsupial in a locality of the Brazilian Cerrado biome.
Subject: maximum likelihood
mixed model
mixture distribution
multivariate count data
Poisson distribution
negative binomial distribution
zero-inflated data
Country: Inglaterra
Editor: Taylor & Francis Ltd
Citation: Journal Of Applied Statistics. Taylor & Francis Ltd, v. 40, n. 7, n. 1586, n. 1596, 2013.
Rights: fechado
Identifier DOI: 10.1080/02664763.2013.789098
Date Issue: 2013
Appears in Collections:Unicamp - Artigos e Outros Documentos

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.