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Bootstrapping Analysis of Lifetime Data with Subsampling
Author(s) -
Wang Guodong,
Niu Zhanwen,
Lv Shanshan,
Qu Liang,
He Zhen
Publication year - 2016
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.1925
Subject(s) - bootstrapping (finance) , percentile , reliability (semiconductor) , computer science , weibull distribution , confidence interval , statistics , data mining , reliability engineering , mathematics , econometrics , power (physics) , engineering , physics , quantum mechanics
Because of cost and time limitations, reliability experiments frequently contain subsampling, which is a restriction on randomization. A two‐stage approach can analyze right censored Weibull distributed reliability data with subsampling. However, in implementing such a method, we found that it did not address the problems of how to perform confidence intervals of low percentiles and reduce the bias of estimates. In this paper, we present a two‐stage bootstrapping approach and an unbiasing factor approach to solve the aforementioned problems. An example is provided to illustrate the proposed method. In addition, the proposed method is compared with existing methods through simulation. The resulting simulations show that the proposed method performs well in low percentiles. Copyright © 2015 John Wiley & Sons, Ltd.