Statistical analysis of competing risks lifetime data from Nadarajaha and Haghighi distribution under type-II censoring

Almarashi, Abdullah M.; Algarni, Ali; Abd-Elmougod, G. A.

doi:10.3233/jifs-179546

Cited by 12 publications

(6 citation statements)

References 21 publications

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“…Recently, the problem of comparing two (or more) different censoring plans has also received considerable attention, among several authors see for example. 32, However, in order to determine the optimum progressive censoring plan, some commonly-used criteria are considered and reported in Table 2.…”

Section: Optimum Progressive Censoring Planmentioning

confidence: 99%

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Statistical reliability analysis of electronic devices using generalized progressively hybrid censoring plan

Elshahhat

Azm

2022

Quality & Reliability Eng

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Generalized progressive hybrid censoring plan proposed to overcome the limitation of the progressive hybrid censoring scheme is that it cannot be applied when very few failures may occur before pre-specified terminal time 𝑇. In this paper, the estimating problems of the model parameters, reliability and hazard rate functions of Nadarajah-Haghighi distribution when a sample is available from generalized progressive hybrid censoring have been considered. The maximum likelihood and Bayes estimators have been obtained for any function of the model parameters. Approximate confidence intervals for the unknown parameters and any function of them are constructed. Using independent gamma informative priors, the Bayes estimators of the unknown parameters are derived under the squared-error loss function. Two approximation techniques, namely: Lindley approximation method and Metropolis Hastings algorithm have been used to carry out the Bayes estimates and also to construct the associate highest posterior density credible intervals. The performance of the proposed methods are evaluated through a Monte Carlo simulation study. To select the optimum censoring scheme among different competing censoring plans, different optimality criteria have been considered. A real-life dataset, representing the failure times of electronic devices, is analyzed to demonstrate how the applicability of the proposed methodologies in real phenomenon.

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Section: Optimum Progressive Censoring Planmentioning

confidence: 99%

“…31 discussed the NHD parameters under Type-II censoring with competing risks. 32 obtained the MLEs and BEs of the unknown parameters and reliability characteristics of the NHD in presence of progressive first-failure censored data.…”

Section: Introductionmentioning

confidence: 99%

Statistical reliability analysis of electronic devices using generalized progressively hybrid censoring plan

Elshahhat

Azm

2022

Quality & Reliability Eng

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“…It is assumed that the N independent elements undergo a lifetime test, with k taken into account prior the experiment, [29]. The initial failure, T 1:k , as well as the cause of the failure, δ 1 , are both recorded.…”

Section: Competing Risks Under Type II Censored Datamentioning

confidence: 99%

Bayesian and non-Bayesian estimation methods to independent competing risks models with type II half logistic weibull sub-distributions with application to an automatic life test

et al. 2022

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In the survival data analysis, competing risks are commonly overlooked, and conventional statistical methods are used to analyze the event of interest. There may be more than one cause of death or failure in many experimental investigations of survival analysis. A competing risks model will be derived statistically applying Type-II half logistic weibull sub-distributions. Type-II half logistic weibull life?times failure model with independent causes. It is possible to estimate parameters and parametric functions using Bayesian and classical methods. A Bayes estimation is obtained by the Markov chain Monte-Carlo method. The posterior density function and the Metropolis-Hasting algorithm are used to calculate the Markov chain Monte-Carlo samples. Simulation data is used to evaluate the performance of the two methods according to the Type-II censored system. As a test of the discussed model, a real data set is provided.

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“…Assuming n = 99, m = 50 and τ = 0.7, the competing risks of the type I HCS are summarized by t = {(0.04, 2), (0.042, 2), (0.051, 2), (0.062, 2), (0.159, 1), (0.163, 2), (0.179, 2), (0.189, 1), (0.191, 1), (0.198, 1), (0.200, 1), (0.206, 2), (0.207, 1), (0.220, 1), (0.222, 2), (0.228, 2), (0.235, 1), (0.245, 1), (0.249, 2), (0.250, 1), (0.252, 2), (0.256, 1), (0.261, 1), (0.265, 1), (0.266, 1), (0.28, 1), (0.282, 2), (0.317, 1), (0.318, 1), (0.324, 2), (0.333, 2), (0.341, 2), (0.343, 1), (0.356, 1), (0.366, 2), (0.383, *), (0.385, *), (0.399, *), (0.403, 1), (0.407, 2), (0.414, 1), (0.420, 2), (0.428, 1), (0.431, 2), (0.432, 1), (0.441 2), (0.461, 2), (0.462, 2), (0.482, 2), (0.495, 1)}}. That is, the type I HCS competing risks have (n 1 , n 2 , n 3 , r) = (24,23,3,50).…”

Section: Example 1: a Disease Data Setmentioning

confidence: 99%

“…Additionally, some applicatiosn of distribution have been introduced by Kayal et al [16]. More details about the competing risks model can be seen in [17][18][19][20][21][22][23][24][25][26][27][28][29], and the references cited therein.…”

Section: Introductionmentioning

confidence: 99%

Burr XII Distribution for Disease Data Analysis in the Presence of a Partially Observed Failure Mode

et al. 2022

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Modeling competing failure modes is an important problem in engineering and survival analyses. Competing failure modes are partially observed in many applications and often pose a modeling challenge. This study discusses the inference for partially observed failure modes assuming a Burr XII distribution. In particular, we consider two failure modes, and the failure time data are collected under a hybrid type I censoring scheme. The model parameters are estimated using maximum likelihood and Bayesian methods under a symmetric squared error loss function, whereas the intervals estimation is done with three methods: asymptotic and credible confidence intervals. Besides a simulation study, a real-life data set is taken from individuals who live in an environment with several diseases to present the utility of the work. Additionally, a simulation study is constructed to measure and compare different estimation methods.

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Statistical analysis of competing risks lifetime data from Nadarajaha and Haghighi distribution under type-II censoring

Cited by 12 publications

References 21 publications

Statistical reliability analysis of electronic devices using generalized progressively hybrid censoring plan

Statistical reliability analysis of electronic devices using generalized progressively hybrid censoring plan

Bayesian and non-Bayesian estimation methods to independent competing risks models with type II half logistic weibull sub-distributions with application to an automatic life test

Burr XII Distribution for Disease Data Analysis in the Presence of a Partially Observed Failure Mode

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