The optimal scheme in type II progressive censoring with random removals for the Rayleigh distribution based on two-sample Bayesian prediction and cost function

Document Type : Original Paper

Authors

1 Department of Mathematics and Applications, Faculty of Basic Sciences, Kosar University of Bojnord, Bojnord, Iran

2 Department of Industrial Engineering, Kosar University of Bojnord, Bijnord, Iran

Abstract

A type II progressive censoring scheme is one of the censoring methods that is important in life-testing studies. This method of censoring allows the experimenter to withdraw some of the tested units at different stages of testing. One question that arises when designing a type II progressive censoring is how we can decide to remove several units from the test at each step? Different answers can be made to answer this question by considering different criteria. In this paper, assuming the censoring scheme is a random variable from Binomial distribution, we intend to obtain the optimal parameter for the distribution of censoring scheme when the distribution is the Rayleigh distribution by considering two criteria, the cost of testing and the Mean squared prediction error in the two-sample prediction problem. To illustrate the effectiveness of the results, a simulation study and a real data example are presented with the help of MATLAB software.

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References

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Balakrishnan, N. and Aggarwala, R. (2000). Progressive
Censoring: Theory, Methods and Applications. Birkhauser, Boston.
Balakrishnan, N. (2007). Progressive censoring methodology: an
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 Balakrishnan, N. and Cramer, E. (2014). The Art of Progressive
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Journal of Advanced Mathematical Modeling
Volume 10, Issue 1
May 2020
Pages 135-157

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History

  • Receive Date: 18 April 2019
  • Revise Date: 05 November 2019
  • Accept Date: 17 January 2020

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