An extension of Birnbaum-Saunders distributions based on scale mixtures of skew-normal distributions with applications to regression models

• Ano de defesa: 2018
• Autor(a) principal: Sánchez, Rocio Paola Maehara
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Algoritmo EM; Análise de influência; Birnbaum-Saunders distribution; Case-deletion; Distribuição Birnbaum-Saunders; Distribuição misturas de escala skew-normal; Distribuição senh-normal; Distribuição skew-normal; Distribuição skew-normal/Independente; Eliminação de casos; EM algorithm; Estimação robusta; Influence analysis; Influência local; Local influence; Nonlinear regression; Regressão não linear; Robust estimation; Scale mixtures of skew-normal distributions; Sinh-normal distribution; Skew-normal distribution; Skew-normal/independent distribution
• Link de acesso: http://www.teses.usp.br/teses/disponiveis/45/45133/tde-14052018-202935/

The aim of this work is to present an inference and diagnostic study of an extension of the lifetime distribution family proposed by Birnbaum and Saunders (1969a,b). This extension is obtained by considering a skew-elliptical distribution instead of the normal distribution. Specifically, in this work we develop a Birnbaum-Saunders (BS) distribution type based on scale mixtures of skew-normal distributions (SMSN). The resulting family of lifetime distributions represents a robust extension of the usual BS distribution. Based on this family, we reproduce the usual properties of the BS distribution, and present an estimation method based on the EM algorithm. In addition, we present regression models associated with the BS distributions (based on scale mixtures of skew-normal), which are developed as an extension of the sinh-normal distribution (Rieck and Nedelman, 1991). For this model we consider an estimation and diagnostic study for uncensored data.