Bivariate step-stress accelerated life test for a new three-parameter model under progressive censored schemes with application in medical

Naif Alotaibi; A. S. Al-Moisheer; Ibrahim Elbatal; Salem A. Alyami; Ahmed M. Gemeay; Ehab M. Almetwally; Naif Alotaibi; A. S. Al-Moisheer; Ibrahim Elbatal; Salem A. Alyami; Ahmed M. Gemeay; Ehab M. Almetwally

doi:10.3934/math.2024173

AIMS Mathematics

2024, Volume 9, Issue 2: 3521-3558. doi: 10.3934/math.2024173

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Bivariate step-stress accelerated life test for a new three-parameter model under progressive censored schemes with application in medical

1.
Department of Mathematics and Statistics, Faculty of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia
2.
Department of Mathematics, College of Science, Jouf University, P.O. Box 848, Sakaka 72351, Saudi Arabia
3.
Department of Mathematics, Faculty of Science, Tanta University, Tanta 31527, Egypt
4.
Faculty of Business Administration, Delta University for Science and Technology, Gamasa 11152, Egypt

Received: 19 November 2023 Revised: 17 December 2023 Accepted: 21 December 2023 Published: 08 January 2024
MSC : 62N05, 62H05, 62F15

In this article, a new three-parameter lifetime model called the Gull alpha power exponentiated exponential (GAPEE) distribution is introduced and studied by combining the Gull alpha power family of distributions and the exponentiated exponential distribution. The shapes of the probability density function (PDF) for the GAPEE distribution can be asymmetric shapes, like unimodal, decreasing, and right-skewed. In addition, the shapes of the hazard rate function (hrf) for the GAPEE distribution can be increasing, decreasing, and upside-down shaped. Several statistical features of the GAPEE distribution are computed. Eight estimation methods such as the maximum likelihood, Anderson-Darling, right-tail Anderson-Darling, left-tailed Anderson-Darling, Cramér-von Mises, least-squares, weighted least-squares, and maximum product of spacing are discussed to estimate the parameters of the GAPEE distribution. The flexibility and the importance of the GAPEE distribution were demonstrated utilizing three real-world datasets related to medical sciences. The GAPEE distribution is extremely adaptable and outperforms several well-known statistical models. A bivariate step-stress accelerated life test based on progressive type-I censoring using the model is presented. Minimizing the asymptotic variance of the maximum likelihood estimate of the log of the scale parameter at design stress under progressive type-I censoring yields an expression for the ideal test plan under progressive type-I censoring.
- exponentiated exponential distribution,
- Gull alpha power family of distributions,
- bivariate step-stress,
- maximum likelihood estimation,
- progressive type-I censoring,
- symmetric,
- asymmetric,
- accelerated life test
Citation: Naif Alotaibi, A. S. Al-Moisheer, Ibrahim Elbatal, Salem A. Alyami, Ahmed M. Gemeay, Ehab M. Almetwally. Bivariate step-stress accelerated life test for a new three-parameter model under progressive censored schemes with application in medical[J]. AIMS Mathematics, 2024, 9(2): 3521-3558. doi: 10.3934/math.2024173

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Abstract

In this article, a new three-parameter lifetime model called the Gull alpha power exponentiated exponential (GAPEE) distribution is introduced and studied by combining the Gull alpha power family of distributions and the exponentiated exponential distribution. The shapes of the probability density function (PDF) for the GAPEE distribution can be asymmetric shapes, like unimodal, decreasing, and right-skewed. In addition, the shapes of the hazard rate function (hrf) for the GAPEE distribution can be increasing, decreasing, and upside-down shaped. Several statistical features of the GAPEE distribution are computed. Eight estimation methods such as the maximum likelihood, Anderson-Darling, right-tail Anderson-Darling, left-tailed Anderson-Darling, Cramér-von Mises, least-squares, weighted least-squares, and maximum product of spacing are discussed to estimate the parameters of the GAPEE distribution. The flexibility and the importance of the GAPEE distribution were demonstrated utilizing three real-world datasets related to medical sciences. The GAPEE distribution is extremely adaptable and outperforms several well-known statistical models. A bivariate step-stress accelerated life test based on progressive type-I censoring using the model is presented. Minimizing the asymptotic variance of the maximum likelihood estimate of the log of the scale parameter at design stress under progressive type-I censoring yields an expression for the ideal test plan under progressive type-I censoring.

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