Abstract
The present paper is aimed at developing Bayesian and Maximum Likelihood estimations (ML) of the Burr type-X model of distribution when data are gathered from Type-II cumulative censoring with binomial eliminations. The procedures for getting the (ML) evaluations of the parameters are examined. The Bayes technique to get both point and interval estimators of the parameters are illustrated. The expected termination time for Type-II cumulative censoring with binomial eliminations is analyzed after carrying out the computation. Classical and Bayes procedures are improved in the case of parameter estimation and evaluated the expected test time for Burr-X model under cumulative censoring wit binomial sweep. A simulation study is performed to compare the implementation of the various procedures and for the expected termination time of the test. Finally, illustrative examples are given and the results from emulation studies determining the achievement of the suggested techniques are presented.
Highlights
Censoring is normal in life-distribution research due to limits and other constraints on data gathering
For some related classical estimation on cumulative Type-II censoring with random cancellations or binomial eliminations, one may refer to Tse et al (2000; Wu, 2003)
We remark that the Mean Square Error (MSE) of all estimates of the variables θ and p become smaller while the elimination probability p is large
Summary
Censoring is normal in life-distribution research due to limits and other constraints on data gathering. Ahmad et al (2015) obtained a Bayes estimates of the parameters and MLE for Burr-X model in the case of double type-II censored specimen of dual generalized order statistics. Classical and Bayesian techniques are expanded in the case of parameter assessment and evaluated the expected test time for Burr-X distribution under cumulative censoring with binomial eliminations. The methods for getting the MLE’s of the parameters θ and p in the context of gradually Type-II censoring information with binomial eliminations are considered Interval and both point estimations of the parameters are obtained. Carrying out the expectation on the life hand side and the right side of Equation 25 with respect to the R, the anticipated ending point for gradually type-II censoring with binomial cancellations is estimated from the following equation:. The ratio of the expected time under various schemes to the expected time under entire sampling, i.e., Ratio of Expected Experiment Times (REET) is defined in (Al-Hossain, 2015b)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
