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Biometrika 1995 82(2):439-446; doi:10.1093/biomet/82.2.439
© 1995 by Biometrika Trust
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MISCELLANEA

Bayesian methods for categorical data under informative general censoring

CARLOS DANIEL MIMOSO PAULINO and CARLOS ALBERTO DE BRAGANÇA PEREIRA

Universidade Técnica de Lisboa, Departamento de Matemática, Instituto Superior Técnico, Centro de Análise e Processamento de Sinais Av. Rovisco Pais, 1096 Lisboa Codex, Portugal
Universidade de São Paulo, Departamento de Estatistica, Instituto de Matemática e Estatistica Caixa Postal 66.281, CEP 09389-970, São Paulo, Brasil

This paper develops a Bayesian approach to the problem of incomplete categorical data informatively censored where the reported sets are not restricted to follow any specific pattern. It generalises that introduced by Paulino & Pereira (1992) in not requiring a censoring pattern by partitions of the set of sampling categories. Some extensions are also discussed.

Key Words: Bayesian analysis • Dirichlet and generalised Dirichlet distributions • Informative censoring process • Unidentifiability


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