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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

L-Logistic regression models: Prior sensitivity analysis, robustness to outliers and applications

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Autor(es):
da Paz, Rosineide F. [1] ; Balakrishnan, Narayanaswamy [2] ; Bazan, Jorge Luis [3]
Número total de Autores: 3
Afiliação do(s) autor(es):
[1] Univ Fed Ceara, Campus Russas, Fortaleza, CE - Brazil
[2] McMaster Univ, Hamilton, ON - Canada
[3] Uninversidade Sao Paulo, Sao Carlos, SP - Brazil
Número total de Afiliações: 3
Tipo de documento: Artigo Científico
Fonte: BRAZILIAN JOURNAL OF PROBABILITY AND STATISTICS; v. 33, n. 3, p. 455-479, AUG 2019.
Citações Web of Science: 0
Resumo

Tadikamalla and Johnson {[}Biometrika 69 (1982) 461-465] developed the L(B )distribution to variables with bounded support by considering a transformation of the standard Logistic distribution. In this manuscript, a convenient parametrization of this distribution is proposed in order to develop regression models. This distribution, referred to here as L-Logistic distribution, provides great flexibility and includes the uniform distribution as a particular case. Several properties of this distribution are studied, and a Bayesian approach is adopted for the parameter estimation. Simulation studies, considering prior sensitivity analysis, recovery of parameters and comparison of algorithms, and robustness to outliers are all discussed showing that the results are insensitive to the choice of priors, efficiency of the algorithm MCMC adopted, and robustness of the model when compared with the beta distribution. Applications to estimate the vulnerability to poverty and to explain the anxiety are performed. The results to applications show that the L-Logistic regression models provide a better fit than the corresponding beta regression models. (AU)

Processo FAPESP: 17/15452-5 - Novos modelos de regressão para dados com resposta binária e/ou limitada
Beneficiário:Jorge Luis Bazan Guzman
Linha de fomento: Bolsas no Exterior - Pesquisa