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Nonparametric prediction intervals for progressive type-II censored order statistics based on \(k\)-records. (English) Zbl 1306.65027

Summary: In this paper, we consider the prediction problem in two-sample case and study the non-parametric predicting future progressively Type-II censored order statistics based on observed \(k\)-records from the same distribution. Also, prediction intervals for progressively Type-II censored spacings are obtained based on \(k\)-record spacings. It is shown that the coverage probabilities of these intervals are exact and do not depend on the underlying distribution. Moreover, optimal prediction intervals are derived for each case. Finally, for illustrating the proposed procedure, we consider a real data set and numerical computations are given. The results of J. Ahmadi and N. Balakrishnan [Statistics 44, No. 4, 417–430 (2010; Zbl 1283.62102)] can be achieved as special cases of our results.

MSC:

62-08 Computational methods for problems pertaining to statistics

Citations:

Zbl 1283.62102
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References:

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