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The Exponentiated Lindley Geometric Distribution with Applications

We introduce a new three-parameter lifetime distribution, the exponentiated Lindley geometric distribution, which exhibits increasing, decreasing, unimodal, and bathtub shaped hazard rates. We provide statistical properties of the new distribution, including shape of the probability density function...

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Detalles Bibliográficos
Autores principales: Peng, Bo, Xu, Zhengqiu, Wang, Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514999/
https://www.ncbi.nlm.nih.gov/pubmed/33267224
http://dx.doi.org/10.3390/e21050510
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author Peng, Bo
Xu, Zhengqiu
Wang, Min
author_facet Peng, Bo
Xu, Zhengqiu
Wang, Min
author_sort Peng, Bo
collection PubMed
description We introduce a new three-parameter lifetime distribution, the exponentiated Lindley geometric distribution, which exhibits increasing, decreasing, unimodal, and bathtub shaped hazard rates. We provide statistical properties of the new distribution, including shape of the probability density function, hazard rate function, quantile function, order statistics, moments, residual life function, mean deviations, Bonferroni and Lorenz curves, and entropies. We use maximum likelihood estimation of the unknown parameters, and an Expectation-Maximization algorithm is also developed to find the maximum likelihood estimates. The Fisher information matrix is provided to construct the asymptotic confidence intervals. Finally, two real-data examples are analyzed for illustrative purposes.
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spelling pubmed-75149992020-11-09 The Exponentiated Lindley Geometric Distribution with Applications Peng, Bo Xu, Zhengqiu Wang, Min Entropy (Basel) Article We introduce a new three-parameter lifetime distribution, the exponentiated Lindley geometric distribution, which exhibits increasing, decreasing, unimodal, and bathtub shaped hazard rates. We provide statistical properties of the new distribution, including shape of the probability density function, hazard rate function, quantile function, order statistics, moments, residual life function, mean deviations, Bonferroni and Lorenz curves, and entropies. We use maximum likelihood estimation of the unknown parameters, and an Expectation-Maximization algorithm is also developed to find the maximum likelihood estimates. The Fisher information matrix is provided to construct the asymptotic confidence intervals. Finally, two real-data examples are analyzed for illustrative purposes. MDPI 2019-05-20 /pmc/articles/PMC7514999/ /pubmed/33267224 http://dx.doi.org/10.3390/e21050510 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Peng, Bo
Xu, Zhengqiu
Wang, Min
The Exponentiated Lindley Geometric Distribution with Applications
title The Exponentiated Lindley Geometric Distribution with Applications
title_full The Exponentiated Lindley Geometric Distribution with Applications
title_fullStr The Exponentiated Lindley Geometric Distribution with Applications
title_full_unstemmed The Exponentiated Lindley Geometric Distribution with Applications
title_short The Exponentiated Lindley Geometric Distribution with Applications
title_sort exponentiated lindley geometric distribution with applications
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514999/
https://www.ncbi.nlm.nih.gov/pubmed/33267224
http://dx.doi.org/10.3390/e21050510
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