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Constructing exact tolerance intervals for the exponential distribution based on record values
Author(s) -
Guo Baocai,
Zhu Naifan,
Wang Wei,
Wang Hsiuying
Publication year - 2020
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.2704
Subject(s) - frequentist inference , bayesian probability , computer science , exponential distribution , data mining , data quality , exponential function , statistics , algorithm , mathematics , bayesian inference , artificial intelligence , engineering , mathematical analysis , metric (unit) , operations management
Abstract Recently, with the wide application of tolerance intervals (TIs), especially in quality management, the construction of TIs has attracted increasing attention. However, TIs applied to record data have not been well established as they have been for complete data. In many industrial stress tests, only record data are stored instead of complete data, which leads to the fact that the developments of methods based on record data are as important as those based on complete data. In this paper, we propose the exact two‐sided TIs for the exponential distribution based on record values from the frequentist and Bayesian perspectives. The accuracy of each type of TIs is quantified. The results show that the Bayesian approach is superior to the frequentist approach in terms of the accuracy. A real data example is used to illustrate the constructions and implementations of the proposed TIs.