The exponentiated generalized family of continuous distributions

Detalhes bibliográficos
Ano de defesa: 2017
Autor(a) principal: ANDRADE, Thiago Alexandro Nascimento de
Orientador(a): CORDEIRO, Gauss Moutinho
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Pernambuco
Programa de Pós-Graduação: Programa de Pos Graduacao em Estatistica
Departamento: Não Informado pela instituição
País: Brasil
Palavras-chave em Português:
Link de acesso: https://repositorio.ufpe.br/handle/123456789/23659
Resumo: Statistical and applied researchers have shown great interest in building new extended probability models that generalize well-known distributions and are more flexible for data modeling in many fields of applications. Probably, one of the most popular ways to extend well-known models is to consider distribution generators. Aclass of univariate distributions called the exponentiated generalized (EG for short) class was recently proposed in the literature. We believe that the EG class of distributions can be widely used to generalize continuous distributions. For this reason, the present doctoral thesis presents some extended models using the EG class. For each model presented in the chapters that follow, we provide a complete mathematical treatment, simulation studies and applications to real data that illustrate the usefulness of the model sunder study.