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Doctoral Thesis
DOI
10.11606/T.11.2018.tde-01082018-154641
Document
Author
Full name
Ricardo Klein Sercundes
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
Piracicaba, 2018
Supervisor
Committee
Demetrio, Clarice Garcia Borges (President)
Lobos, Cristian Marcelo Villegas
Motta, Mariana Rodrigues
Vieira, Afrânio Márcio Corrêa
Zocchi, Silvio Sandoval
Title in English
Flexible models for hierarchical and overdispersed data in agriculture
Keywords in English
B-spline
Beta distribution
Combined model
Generalized linear mixed model
Likelihood
Multinomial distribution
Abstract in English
In this work we explored and proposed flexible models to analyze hierarchical and overdispersed data in agriculture. A semi-parametric generalized linear mixed model was applied and compared with the main standard models to assess count data and, a combined model that take into account overdispersion and clustering through two separate sets of random effects was proposed to model nominal outcomes. For all models, the computational codes were implemented using the SAS software and are available in the appendix.
Title in Portuguese
Modelos flexíveis para dados hierárquicos e superdispersos na agricultura
Keywords in Portuguese
B-spline
Distribuição beta
Distribuição multinomial
Modelo combinado
Modelo linear generalizado misto
Verossimilhança
Abstract in Portuguese
Nesse trabalho, exploramos e propusemos modelos flexíveis para a análise de dados hierárquicos e superdispersos na agricultura. Um modelo linear generalizado semi- paramétrico misto foi aplicado e comparado com os principais modelos para a análise de dados de contagem e, um modelo combinado que leva em consideração a superdispersão e a hierarquia dos dados por meio de dois efeitos aleatórios distintos foi proposto para a análise de dados nominais. Todos os códigos computacionais foram implementados no software SAS sendo disponibilizados no apêndice.
 
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Release Date
2020-08-14
Publishing Date
2018-08-28
 
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