Prediction of times to failure of censored units under generalized progressive hybrid censoring scheme

J. Ahmadi (), B. Khatib Astaneh, M. Rezaie and S. Ameli
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J. Ahmadi: Ferdowsi University of Mashhad
B. Khatib Astaneh: University of Neyshabur
M. Rezaie: University of Birjand
S. Ameli: University of Birjand

Computational Statistics, 2022, vol. 37, issue 4, No 20, 2049-2086

Abstract: Abstract In this paper, the problem of predicting times to failure of units censored in multiple stages of generalized progressively hybrid censoring from exponential and Weibull distributions is discussed. Different classical point predictors, namely, the best unbiased, the maximum likelihood and the conditional median predictors are all derived. Moreover, the problem of interval prediction is investigated. Numerical example as well as two real data sets are used to illustrate the proposed prediction methods. Using a Monte-Carlo simulation algorithm, the performance of the point predictors is investigated in terms of the bias and mean squared prediction error criteria. Also, the width and the coverage rate of the obtained prediction intervals are studied by simulations.

Keywords: Best unbiased predictor; Conditional median predictor; Maximum likelihood predictor; Mean squared prediction error; Monte-Carlo simulation; Prediction interval (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:compst:v:37:y:2022:i:4:d:10.1007_s00180-021-01191-3

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DOI: 10.1007/s00180-021-01191-3

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