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Doctoral Thesis
DOI
10.11606/T.95.2007.tde-16062008-130319
Document
Author
Full name
Marcelo de Souza Lauretto
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2007
Supervisor
Committee
Stern, Julio Michael (President)
Cesar Junior, Roberto Marcondes
Lopez, Luis Fernandez
Pereira, Basilio de Braganca
Pereira, Carlos Alberto de Braganca
Title in Portuguese
Seleção de modelos através de um teste de hipótese genuinamente Bayesiano: misturas de normais multivariadas e hipóteses separadas
Keywords in Portuguese
hipóteses separadas
modelos de misturas
testes de significância
Abstract in Portuguese
Nesta tese propomos o Full Bayesian Significance Test (FBST), apresentado por Pereira e Stern em 1999, para análise de modelos de misturas de normais multivariadas. Estendemos o conceito de modelos de misturas para explorar outro problema clássico em Estatística, o problema de modelos separados. Nas duas propostas, realizamos experimentos numéricos inspirados em problemas biológicos importantes: o problema de classificação não supervisionada de genes baseada em seus níveis de expressão, e o problema da discriminação entre os modelos Weibull e Gompertz - distribuições clássicas em análise de sobrevivência.
Title in English
Model selection by a genuinely Bayesian significance test: Multivariate normal mixtures and separated hypotheses
Keywords in English
mixture models
separated hypotheses
Significance tests
Abstract in English
In this thesis we propose the Full Bayesian Significance Test (FBST) as a tool for multivariate normal mixture models. We extend the fundamental mixture concepts to another important problem in Statistics, the problem of separate models. In both methods, we perform numerical experiments based on important biological problems: the unsupervised classification of genes based on their expression profiles, and the problem of deciding between the Weibull and Gompertz models - two classical distributions widely used in survival analysis.
 
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lauretto.pdf (776.98 Kbytes)
Publishing Date
2009-02-02
 
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