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Doctoral Thesis
DOI
10.11606/T.45.2008.tde-08072008-110122
Document
Author
Full name
Iracema Hiroko Iramina Arashiro
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2008
Supervisor
Committee
Lima, Antonio Carlos Pedroso de (President)
Cancho, Vicente Garibay
Louzada Neto, Francisco
Singer, Julio da Motta
Valença, Dione Maria
Title in Portuguese
Modelo multi-estados markoviano não homogêneo com efeitos dinâmicos
Keywords in Portuguese
coeficiente dependente do tempo
estimador de crivo
modelos multi-estados.
Abstract in Portuguese
Modelos multi-estados têm sido utilizados para descrever o comportamento de unidades amostrais cuja principal resposta é o tempo necessário para a ocorrência de seqüências de eventos. Consideramos um modelo multi-estados markoviano, não homogêneo, que incorpora covariáveis cujos efeitos podem variar ao longo do tempo (efeitos dinâmicos), o que permite a generalização dos modelos usualmente empregados. Resultados assintóticos mostram que procedimentos de estimação baseados no método histograma crivo convergem para um processo gaussiano. A metodologia proposta mostra-se adequada na modelagem de dados reais para comparação de desenvolvimento de recém-nascidos pré-termo com os a termo. Estudos com dados gerados artificialmente confirmam os resultados teóricos obtidos.
Title in English
Non-homogeneous Markov models with dynamic effects.
Keywords in English
Histogram sieves
multi state models
time-dependent coefficient.
Abstract in English
Multi-state models have been used to describe the behavior of sample units where the principal response is the time needed for the occurrence of a sequence of events. We consider a non-homogeneous Markovian multi-state model that incorporates covariates with time-dependent coefficient (dynamic effects), generalizing models usually employed. The asymptotic results show that the estimators based on the method of histogram sieves converge to a Gaussian process. The proposed methodology revels adequated for modeling data related to the comparison of developement of preterm infants with term infants. The studies with artificially generated data confirm the asymptotic results.
 
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Iracema_tese_corr.pdf (607.33 Kbytes)
Publishing Date
2008-08-07
 
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