A new Gompertz-three-parameter-lindley distribution for modeling survival time data

In this paper, a new survival distribution is introduced. It is a mixture of the Gompertz distribution and three-parameter-Lindley distribution. The statistical properties of the proposed distribution including the shape properties, cumulative distribution, quantile functions, moment generating func...

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Main Authors: Liang, Fei, Lu, Hezhi, Xi, Yuhang
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2025
Online Access:http://journalarticle.ukm.my/25218/
http://journalarticle.ukm.my/25218/1/SMD%2023.pdf
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author Liang, Fei
Lu, Hezhi
Xi, Yuhang
author_facet Liang, Fei
Lu, Hezhi
Xi, Yuhang
author_sort Liang, Fei
building UKM Institutional Repository
collection Online Access
description In this paper, a new survival distribution is introduced. It is a mixture of the Gompertz distribution and three-parameter-Lindley distribution. The statistical properties of the proposed distribution including the shape properties, cumulative distribution, quantile functions, moment generating function, failure rate function, mean residual function, and stochastic orders are studied. Moreover, a new regression model based on the proposed distribution is presented. Maximum likelihood estimators (MLEs) of unknown parameters are obtained via differential evolution algorithms, and simulation studies are conducted to evaluate the consistency of the MLEs. Finally, the proposed model and its regression model are applied to a real dataset and compared with other well-known models, demonstrating their superior performance, particularly for heavy-tailed data.
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spelling oai:generic.eprints.org:252182025-05-13T12:18:28Z http://journalarticle.ukm.my/25218/ A new Gompertz-three-parameter-lindley distribution for modeling survival time data Liang, Fei Lu, Hezhi Xi, Yuhang In this paper, a new survival distribution is introduced. It is a mixture of the Gompertz distribution and three-parameter-Lindley distribution. The statistical properties of the proposed distribution including the shape properties, cumulative distribution, quantile functions, moment generating function, failure rate function, mean residual function, and stochastic orders are studied. Moreover, a new regression model based on the proposed distribution is presented. Maximum likelihood estimators (MLEs) of unknown parameters are obtained via differential evolution algorithms, and simulation studies are conducted to evaluate the consistency of the MLEs. Finally, the proposed model and its regression model are applied to a real dataset and compared with other well-known models, demonstrating their superior performance, particularly for heavy-tailed data. Penerbit Universiti Kebangsaan Malaysia 2025 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/25218/1/SMD%2023.pdf Liang, Fei and Lu, Hezhi and Xi, Yuhang (2025) A new Gompertz-three-parameter-lindley distribution for modeling survival time data. Sains Malaysiana, 54 (3). pp. 927-941. ISSN 0126-6039 https://www.ukm.my/jsm/english_journals/vol54num3_2025/contentsVol54num3_2025.html
spellingShingle Liang, Fei
Lu, Hezhi
Xi, Yuhang
A new Gompertz-three-parameter-lindley distribution for modeling survival time data
title A new Gompertz-three-parameter-lindley distribution for modeling survival time data
title_full A new Gompertz-three-parameter-lindley distribution for modeling survival time data
title_fullStr A new Gompertz-three-parameter-lindley distribution for modeling survival time data
title_full_unstemmed A new Gompertz-three-parameter-lindley distribution for modeling survival time data
title_short A new Gompertz-three-parameter-lindley distribution for modeling survival time data
title_sort new gompertz-three-parameter-lindley distribution for modeling survival time data
url http://journalarticle.ukm.my/25218/
http://journalarticle.ukm.my/25218/
http://journalarticle.ukm.my/25218/1/SMD%2023.pdf