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Reliability Analysis of HEE Parameters via progressive type-ii censoring with Applications

Computer Modeling in Engineering & Sciences 2023年第12期137卷 2761-2793页

作者： Heba S.Mohammed Mazen Nassar Refah Alotaibi Ahmed Elshahhat Department of Mathematical Sciences College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Statistics Faculty of ScienceKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Statistics Faculty of CommerceZagazig UniversityZagazigEgypt Faculty of Technology and Development Zagazig UniversityZagazig44519Egypt

A new extended exponential lifetime model called Harris extended-exponential(HEE)distribution for data modelling with increasing and decreasing hazard rate shapes has been *** the reliability context,researchers prefer to use censoring plans to collect data in order to achieve a compromise between total test time and/or test sample ***,this study considers both maximum likelihood and Bayesian estimates of the Harris extended-exponential distribution parameters and some of its reliability indices using a progressive type-ii censoring *** the premise of independent gamma priors,the Bayesian estimation is created using the squared-error and general entropy loss *** to the challenging form of the joint posterior distribution,to evaluate the Bayes estimates,samples from the full conditional distributions are generated using Markov Chain Monte Carlo *** each unknown parameter,the highest posterior density credible intervals and asymptotic confidence intervals are also *** a simulated study,the usefulness of the various suggested strategies is *** optimal progressive censoring plans are also shown,and various optimality criteria are *** actual data sets,taken from engineering and veterinary medicine areas,are analyzed to show how the offered point and interval estimators can be used in practice and to verify that the proposed model furnishes a good fit than other lifetimemodels:alpha power exponential,generalized-exponential,Nadarajah-Haghighi,Weibull,Lomax,gamma and exponential *** evaluations revealed that in the presence of progressively type-ii censored data,the Bayes estimation method against the squared-error(symmetric)loss is advised for getting the point and interval estimates of the HEE distribution.

关键词： Harris extended-exponential model progressive type-ii censoring reliability maximum likelihood MCMC techniques Monte Carlo experiments

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Statistical Inference of Chen Distribution Based on Two progressive type-ii censoring Schemes

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Computers, Materials & Continua 2021年第3期66卷 2797-2814页

作者： Hassan M.Aljohani Department of Mathematics&Statistics Faculty of ScienceTaif UniversityTaif21944Saudi Arabia

An inverse problemin practical scientific investigations is the process of computing unknown parameters from a set of observations where the observations are only recorded indirectly,such as monitoring and controlling quality in industrial process *** regression can be thought of as linear inverse *** other words,the procedure of unknown estimation parameters can be expressed as an inverse ***,maximum likelihood provides an unstable solution,and the problembecomes more complicated if unknown parameters are estimated from different ***,researchers search for better *** study two joint censoring schemes for lifetime products in industrial process *** practice,this type of data can be collected in fields such as the medical industry and industrial *** this study,statistical inference for the Chen lifetime products is considered and analyzed to estimate underlying *** likelihood and Bayes’rule are both studied for model *** asymptotic distribution of maximumlikelihood estimators and the empirical distributions obtained withMarkov chainMonte Carlo algorithms are utilized to build the interval *** results using tables and figures are adopted through simulation studies and verified in an analysis of the lifetime *** briefly describe the performance of developed methods.

关键词： Chen distributions progressive type-ii censoring maximum likelihood mean posterior Bayesian estimation MCMC

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Computational Analysis of Novel Extended Lindley progressively Censored Data

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2571-2596页

作者： Refah Alotaibi Mazen Nassar Ahmed Elshahhat Department of Mathematical Sciences College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Statistics Faculty of ScienceKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Statistics Faculty of CommerceZagazig UniversityZagazigEgypt Faculty of Technology and Development Zagazig UniversityZagazig44519Egypt

A novel extended Lindley lifetime model that exhibits unimodal or decreasing density shapes as well as increasing,bathtub or unimodal-then-bathtub failure rates, named the Marshall-Olkin-Lindley (MOL) model is *** this research, using a progressive type-ii censored, various inferences of the MOL model parameters oflife are introduced. Utilizing the maximum likelihood method as a classical approach, the estimators of themodel parameters and various reliability measures are investigated. Against both symmetric and asymmetric lossfunctions, the Bayesian estimates are obtained using the Markov Chain Monte Carlo (MCMC) technique with theassumption of independent gamma priors. From the Fisher information data and the simulatedMarkovian chains,the approximate asymptotic interval and the highest posterior density interval, respectively, of each unknownparameter are calculated. Via an extensive simulated study, the usefulness of the various suggested strategies isassessedwith respect to some evaluationmetrics such as mean squared errors, mean relative absolute biases, averageconfidence lengths, and coverage percentages. Comparing the Bayesian estimations based on the asymmetric lossfunction to the traditional technique or the symmetric loss function-based Bayesian estimations, the analysisdemonstrates that asymmetric loss function-based Bayesian estimations are preferred. Finally, two data sets,representing vinyl chloride and repairable mechanical equipment items, have been investigated to support theapproaches proposed and show the superiority of the proposed model compared to the other fourteen lifetimemodels.

关键词： Marshall-Olkin-Lindleymodel reliability inference Bayesian and classical inference progressive type-ii censoring

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Bayesian Analysis in Partially Accelerated Life Tests for Weighted Lomax Distribution

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Computers, Materials & Continua 2021年第9期68卷 2859-2875页

作者： Rashad Bantan Amal S.Hassan Ehab Almetwally M.Elgarhy Farrukh Jamal Christophe Chesneau Mahmoud Elsehetry Deanship of Scientific Research King Abdulaziz UniversityJeddah21589Kingdom of Saudi Arabia Faculty of Graduate Studies for Statistical Research Cairo UniversityGiza12613Egypt Faculty of Business Administration Delta University of Science and TechnologyMansoura11152Egypt The Higher Institute of Commercial Sciences Al Mahalla Al Kubra31951AlgarbiaEgypt Department of Statistics The Islamia University of BahawalpurPunjab 63100Pakistan Department of Mathematics LMNOUniversity of CaenCaen14032France Deanship of Information Technology King Abdulaziz UniversityJeddah21589Kingdom of Saudi Arabia

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 *** this paper,a step stress partially accelerated life test(SSPALT)is regarded under the progressive type-ii censored data with random *** removals from the test are considered to have the binomial *** life times of the testing items are assumed to follow lengthbiased weighted Lomax *** maximum likelihood method is used for estimating the model parameters of length-biased weighted *** asymptotic confidence interval estimates of the model parameters are evaluated using the Fisher information *** 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 *** precision of the Bayesian estimates and the maximum likelihood estimates are compared by *** addition,to compare the performance of the considered confidence intervals for different parameter values and sample *** 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 ***,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,observed failures,and censoring schemes,in most *** performance comparison is conducted by the experiments with real data.

关键词： Partially accelerated life testing progressive type-ii censoring length-biased weighted Lomax Bayesian and bootstrap confidence intervals

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Estimation in the Complementary Exponential Geometric Distribution Based on progressive type-ii Censored Data

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Communications in Mathematics and Statistics 2020年第4期8卷 409-441页

作者： Ozlem GürünlüAlma Reza Arabi Belaghi Department of Statistics Faculty of SciencesMuğla SıtkıKoçman UniversityMuğlaTurkey Department of Statistics Faculty of Mathematical SciencesUniversity of TabrizTabrizIran

Complementary exponential geometric distribution has many applications in survival and reliability *** to its importance,in this study,we are aiming to estimate the parameters of this model based on progressive type-ii censored *** do this,we applied the stochastic expectation maximization method and Newton-Raphson techniques for obtaining the maximum likelihood *** also considered the estimation based on Bayesian method using several approximate:MCMC samples,Lindely approximation and Metropolis-Hasting *** addition,we considered the shrinkage estimators based on Bayesian and maximum likelihood ***,the HPD intervals for the parameters are constructed based on the posterior samples from the Metropolis-Hasting *** the sequel,we obtained the performance of different estimators in terms of biases,estimated risks and Pitman closeness via Monte Carlo simulation *** paper will be ended up with a real data set example for illustration of our purpose.

关键词： Bayesian analysis Complementary exponential geometric(CEG)distribution progressive type-ii censoring Maximum likelihood estimators SEM algorithm Shrinkage estimator

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