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Master's Dissertation
DOI
10.11606/D.55.2018.tde-22012018-143906
Document
Author
Full name
Emerson Wruck
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2001
Supervisor
Committee
Achcar, Jorge Alberto (President)
Andrade Filho, Marinho Gomes de
Branco, Marcia D Elia
Title in Portuguese
Classificação e discriminação: um enfoque Bayesiano
Keywords in Portuguese
Não disponível
Abstract in Portuguese
Não disponível
Title in English
Not available
Keywords in English
Not available
Abstract in English
ln this dissertation, we present Bayesian alteniatives for classification probiem under different approaches. First of all, we propose a Box and Cox transformation to have normal data to be used in classification problems. We also consider the classification problem assuming a vector X with a mixture of inultivariate normal distributions, using Bayesian procedures to buiid a classification rule. We also consider the classification for binary data and correlated binary data using the Bayesian approach and also introducing randoin effects to capturate the correlation. For the Bayesian approach, we use MCMC methods and we consider the utilization of the software "Ox' as a great altemative for probiems related the efficiency of the algorithm.
 
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EmersonWruck.pdf (32.15 Mbytes)
Publishing Date
2018-01-22
 
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