Estimation in Step-stress Partially Accelerated Life Test for Exponentiated Pareto Distribution under Progressive Censoring with Random Removal

Hassan, Amal S.; Abd-Allah, Marwa; El-Elaa, Hamdy

doi:10.9734/jamcs/2017/34691

Cited by 2 publications

(2 citation statements)

References 7 publications

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“…In constant-stress PALTs each item is run at constant high stress until either failure occurs or the test is terminated. Specifically, SS-PALTs were studied under progressive censoring schemes by several authors; for example, see Ismail and Sarhan (2009); EL-Sagheer and Ahsanullah (2015); Soliman et al (2017); Hassan et al (2017); Mohie EL-Din et al (2021); Yousef et al (2022); Almarashi (2023); Alotaibi et al (2022). In this paper, the samples generated under progressive Type II censoring schemes with binomial removals and accelerated under SS-PALTs from IEL distribution.…”

Section: Introductionmentioning

confidence: 99%

Inference of Inverted Exponentiated Lomax Distribution based on Step-Stress Partially Accelerated Life Test under Progressive Type II Censoring

Assar,

Almetwally

2023

The Egyptian Statistical Journal

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Due to the importance of the problem of testing the product units under stress higher than normal stress conditions, specially used in reliability analysis. In this paper, we discuss the problem of estimation with step stress partially accelerated life tests, the lifetime of testing items under use condition follows the inverted exponentiated Lomax distribution. The test is running under progressive Type-II censoring scheme, and the units drawn from the test were distributed as a binomial distribution. The model parameters and acceleration factor are estimated by maximum likelihood and Bayesian methods. The corresponding asymptotic confidence intervals as well as credible intervals are also constructed. Also, the theoretical results are assessed and compared through Monte Carlo simulation study. Two real data set are used to illustrate how the approaches will perform in practice. Finally, we reported some comments about numerical computation.

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Section: Introductionmentioning

confidence: 99%

Inference of Inverted Exponentiated Lomax Distribution based on Step-Stress Partially Accelerated Life Test under Progressive Type II Censoring

Assar,

Almetwally

2023

The Egyptian Statistical Journal

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“…Progressive censoring is useful in a life-testing experiment because its ability to remove live units from the experiment saves both time and money. The PALTs have been widely studied for step-stress schemes of type-I, type-II, and progressive type-II censoring (PTIIC) schemes [3][4][5][6][7][8][9][10][11][12].…”

mentioning

confidence: 99%

Bayesian Analysis in Partially Accelerated Life Tests for Weighted Lomax Distribution

Bantan¹,

Hassan²,

Almetwally³

et al. 2021

Computers, Materials &Amp; Continua

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Accelerated life testing has been widely used in product life testing experiments because it can quickly provide information on the lifetime distributions by testing products or materials at higher than basic conditional levels of stress, such as pressure, temperature, vibration, voltage, or load to induce early failures. In this paper, a step stress partially accelerated life test (SS-PALT) is regarded under the progressive type-II censored data with random removals. The removals from the test are considered to have the binomial distribution. The life times of the testing items are assumed to follow lengthbiased weighted Lomax distribution. The maximum likelihood method is used for estimating the model parameters of length-biased weighted Lomax. The asymptotic confidence interval estimates of the model parameters are evaluated using the Fisher information matrix. The Bayesian estimators cannot be obtained in the explicit form, so the Markov chain Monte Carlo method is employed to address this problem, which ensures both obtaining the Bayesian estimates as well as constructing the credible interval of the involved parameters. The precision of the Bayesian estimates and the maximum likelihood estimates are compared by simulations. In addition, to compare the performance of the considered confidence intervals for different parameter values and sample sizes. The Bootstrap confidence intervals give more accurate results than the approximate confidence intervals since the lengths of the former are less than the lengths of latter, for different sample sizes, observed failures, and censoring schemes, in most cases. Also, the percentile Bootstrap confidence intervals give more accurate results than Bootstrap-t since the lengths of the former are less than the lengths of latter for different sample sizes,

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Estimation in Step-stress Partially Accelerated Life Test for Exponentiated Pareto Distribution under Progressive Censoring with Random Removal

Cited by 2 publications

References 7 publications

Inference of Inverted Exponentiated Lomax Distribution based on Step-Stress Partially Accelerated Life Test under Progressive Type II Censoring

Inference of Inverted Exponentiated Lomax Distribution based on Step-Stress Partially Accelerated Life Test under Progressive Type II Censoring

Bayesian Analysis in Partially Accelerated Life Tests for Weighted Lomax Distribution

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