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Improved techniques for parametric and nonparametric evaluations of the first‐passage time for degradation processes
Author(s) -
Palayangoda Lochana K.,
Ng Hon Keung Tony,
Butler Ronald W.
Publication year - 2020
Publication title -
applied stochastic models in business and industry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.413
H-Index - 40
eISSN - 1526-4025
pISSN - 1524-1904
DOI - 10.1002/asmb.2528
Subject(s) - nonparametric statistics , reliability (semiconductor) , parametric statistics , computer science , monte carlo method , degradation (telecommunications) , process (computing) , stochastic process , mathematical optimization , algorithm , econometrics , mathematics , statistics , telecommunications , power (physics) , physics , quantum mechanics , operating system
For degradation data in reliability analysis, estimation of the first‐passage time (FPT) distribution to a threshold provides valuable information on reliability characteristics. Recently, Balakrishnan and Qin (2019; Applied Stochastic Models in Business and Industry , 35:571–590) studied a nonparametric method to approximate the FPT distribution of such degradation processes if the underlying process type is unknown. In this article, we propose some improved techniques based on saddlepoint approximation, which enhance those existing methods. Numerical examples and Monte Carlo simulation studies are used to illustrate the advantages of the proposed techniques. Limitations of the improved techniques are discussed and some possible solutions to such are proposed. Some concluding remarks and practical recommendations are provided based on the results.