Modelo geométrico de ordem k correlacionado

• Ano de defesa: 2019
• Autor(a) principal: Souza, Roberta de
• Orientador(a): Diniz, Carlos Alberto Ribeiro
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs
• Palavras-chave em Português: Distribuições discretas generalizadas; Distribuição geométrica correlacionada; Distribuição geométrica de ordem k; Modelos de regressão; Análise de diagnóstico
• Palavras-chave em Inglês: Generalized discrete distributions; Correlated geometric distribution; Geometric distribution of order k; Regression models; Regression diagnostics
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA
• Link de acesso: https://repositorio.ufscar.br/handle/ufscar/11914

In this work we propose the correlated geometric distribution of order k, k≥1, with parameters π and ρ; π ∈(0,1), max{−1,−1−π π } ≤ρ < 1, as an extension of the generalized geometric distribution proposed by Philippou e Muwafi (1980) and considering the ideas of Kolev, Minkova e Neytchev (2000) for generalizations of discrete distributions by including an additional parameter ρ. Thus, it is also a re-reading of the geometric distribution of order k by Aki e Hirano (1993). Some properties of the proposed distribution are presented. Regression models are developed using classical and Bayesian estimation methods. Simulated data studies show the behavior of the distributions and some properties of the estimators. The main motivation in this research, besides contribute to generalizations of discrete distributions, is to propose na alternative analysis and even more suitable for real data, since the effect of the individual correlation is taken into account through the existence of the parameter. The fitted models are evaluated and the residual analysis and diagnosis of influence or divergence are also presented.