Computational Testing Procedure of the Measure of Performance for Exponentiated Weibull Products under Progressive Type II Right Censoring Scheme

2018 ◽  
Vol 48 (2) ◽  
pp. 20170190
Author(s):  
Jong-Wuu Wu ◽  
Ching-Wen Hong
Keyword(s):  
Testing Procedure ◽  
Right Censoring ◽  
Type Ii ◽  
Progressive Type ◽  
Exponentiated Weibull ◽  
Computational Testing ◽  
Measure Of Performance ◽  
Censoring Scheme

scholarly journals Estimation of the Parameters and Expected Test Time of Exponentiated Weibull Lifetimes Under Type II Progressive Censoring Scheme With Random Removals

2019 ◽  
Vol 8 (2) ◽  
pp. 124
Author(s):  
Fathy H. Eissa ◽  
Shuo-Jye Wu ◽  
Hamid H. Ahmed
Keyword(s):  
Test Time ◽  
Computational Formula ◽  
Type Ii ◽  
Sampling Plans ◽  
Progressive Type ◽  
Exponentiated Weibull Distribution ◽  
Exponentiated Weibull ◽  
Censored Sample ◽  
Censoring Scheme ◽  
Total Test Time

Based on progressive type-II censored sample with random removals, point and interval estimations for the shape parameters of the exponentiated Weibull distribution are discussed. Computational formula for the expected total test time are derived for different situations of sampling plans. This is useful in planning a life test experiment. The efficiency of the estimators are compared in terms of the root mean square error, the variance and the coverage probability of the corresponding confidence intervals. A simulation study is presented for several values of removal probability and different values of failure percentage. Also, numerical applications are conducted to illustrate and compare the usefulness of the different sampling plans in terms of expected test times for different patterns of failure rates.

scholarly journals Different Approaches to Estimation of the Gompertz Distribution under the Progressive Type-II Censoring Scheme

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Kyeongjun Lee ◽  
Jung-In Seo
Keyword(s):  
Nuisance Parameter ◽  
Estimation Method ◽  
Real Data ◽  
Type Ii ◽  
Gompertz Distribution ◽  
Type Ii Censoring ◽  
Scale Parameters ◽  
Progressive Type ◽  
Censoring Scheme ◽  
Progressive Type Ii Censoring

This paper provides an estimation method for an unknown parameter by extending weighted least-squared and pivot-based methods to the Gompertz distribution with the shape and scale parameters under the progressive Type-II censoring scheme, which induces a consistent estimator and an unbiased estimator of the scale parameter. In addition, a way to deal with a nuisance parameter is provided in the pivot-based approach. For evaluation and comparison, the Monte Carlo simulations are conducted, and real data are analyzed.

scholarly journals Assessing the Lifetime Performance Index of Burr Type III Distribution under Progressive Type II Censoring

2021 ◽  
pp. 633-647
Author(s):  
Amal Hassan ◽  
Salwa Assar ◽  
Amany Selmy
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimator ◽  
Performance Index ◽  
Testing Procedure ◽  
Type Ii ◽  
Likelihood Estimator ◽  
Significance Level ◽  
Type Iii ◽  
Lifetime Performance ◽  
Progressive Type

Process capability analysis has been widely applied in the field of quality control to monitor the performance of industrial processes. Hence, lifetime performance index CL is used to measure the potential and performance of a process. In the present study, we construct a maximum likelihood estimator of CL under Burr Type III distribution based on the progressive Type II censored sample. The maximum likelihood estimator of CL is then utilized to develop the hypothesis testing procedure in the condition of known L. Finally, one practical example and Monte Carlo simulation are given to assess the behavior of the lifetime performance index under given significance level.

scholarly journals Bayesian Estimation for Inverse Weibull Distribution Under Progressive Type-II Censored Data With Beta-Binomial Removals

2018 ◽  
Vol 47 (1) ◽  
pp. 77-94
Author(s):  
Pradeep Kumar Vishwakarma ◽  
Arun Kaushik ◽  
Aakriti Pandey ◽  
Umesh Singh ◽  
Sanjay Kumar Singh
Keyword(s):  
Weibull Distribution ◽  
Real Data ◽  
Estimation Procedure ◽  
Type Ii ◽  
Unknown Parameters ◽  
Data Set ◽  
Progressive Type ◽  
Inverse Weibull Distribution ◽  
Type Ii Censored Data ◽  
Censoring Scheme

This paper deals with the estimation procedure for inverse Weibull distribution under progressive type-II censored samples when removals follow Beta-binomial probability law. To estimate the unknown parameters, the maximum likelihood and Bayes estimators are obtained under progressive censoring scheme mentioned above. Bayes estimates are obtained using Markov chain Monte Carlo (MCMC) technique considering square error loss function and compared with the corresponding MLE's. Further, the expected total time on test is obtained under considered censoring scheme.  Finally, a real data set has been analysed to check the validity of the study.

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