The exponentiated generalized standardized half-logistic distribution

We study a new two-parameter lifetime model called the exponentiated generalized standardized half-logistic distribution, which extends the half-logistic pioneered by Balakrishnan in the eighties. We provide explicit expressions for the moments, generating and quantile functions, mean deviations, Bo...

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Principais autores: Cordeiro, Gauss M., Andrade, Thiago A. N. de, Bourguignon, Marcelo, Silva, Frank Gomes
Formato: article
Idioma:English
Publicado em: Canadian Center of Science and Education
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Endereço do item:https://repositorio.ufrn.br/handle/123456789/50048
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spelling ri-123456789-500482022-12-08T20:29:24Z The exponentiated generalized standardized half-logistic distribution Cordeiro, Gauss M. Andrade, Thiago A. N. de Bourguignon, Marcelo Silva, Frank Gomes Exponentiated generalized class Half-logistic distribution Hazard rate function Lifetime distribution Moment We study a new two-parameter lifetime model called the exponentiated generalized standardized half-logistic distribution, which extends the half-logistic pioneered by Balakrishnan in the eighties. We provide explicit expressions for the moments, generating and quantile functions, mean deviations, Bonferroni and Lorenz curves, and order statistics. The model parameters are estimated by the maximum likelihood method. A simulation study reveals that the estimators have desirable properties such as small biases and variances even in moderate sample sizes. We prove empirically that the new distribution provides a better fit to a real data set than other competitive models. 2022-12-08T20:29:22Z 2022-12-08T20:29:22Z 2017-05 article CORDEIRO, Gauss M.; et al. The Exponentiated Generalized Standardized Half-logistic Distribution. International Journal of Statistics and Probability, v. 6, p. 24-42, 2017. Disponível em: http://www.ccsenet.org/journal/index.php/ijsp/article/view/67120. Acesso em: 07 dez. 2017 1927-7032 https://repositorio.ufrn.br/handle/123456789/50048 en Acesso Aberto application/pdf Canadian Center of Science and Education
institution Repositório Institucional
collection RI - UFRN
language English
topic Exponentiated generalized class
Half-logistic distribution
Hazard rate function
Lifetime distribution
Moment
spellingShingle Exponentiated generalized class
Half-logistic distribution
Hazard rate function
Lifetime distribution
Moment
Cordeiro, Gauss M.
Andrade, Thiago A. N. de
Bourguignon, Marcelo
Silva, Frank Gomes
The exponentiated generalized standardized half-logistic distribution
description We study a new two-parameter lifetime model called the exponentiated generalized standardized half-logistic distribution, which extends the half-logistic pioneered by Balakrishnan in the eighties. We provide explicit expressions for the moments, generating and quantile functions, mean deviations, Bonferroni and Lorenz curves, and order statistics. The model parameters are estimated by the maximum likelihood method. A simulation study reveals that the estimators have desirable properties such as small biases and variances even in moderate sample sizes. We prove empirically that the new distribution provides a better fit to a real data set than other competitive models.
format article
author Cordeiro, Gauss M.
Andrade, Thiago A. N. de
Bourguignon, Marcelo
Silva, Frank Gomes
author_facet Cordeiro, Gauss M.
Andrade, Thiago A. N. de
Bourguignon, Marcelo
Silva, Frank Gomes
author_sort Cordeiro, Gauss M.
title The exponentiated generalized standardized half-logistic distribution
title_short The exponentiated generalized standardized half-logistic distribution
title_full The exponentiated generalized standardized half-logistic distribution
title_fullStr The exponentiated generalized standardized half-logistic distribution
title_full_unstemmed The exponentiated generalized standardized half-logistic distribution
title_sort exponentiated generalized standardized half-logistic distribution
publisher Canadian Center of Science and Education
publishDate 2022
url https://repositorio.ufrn.br/handle/123456789/50048
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