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A non‐parametric order statistics software reliability model
Author(s) -
Barghout May,
Littlewood Bev,
AbdelGhaly Abdalla
Publication year - 1998
Publication title -
software testing, verification and reliability
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.216
H-Index - 49
eISSN - 1099-1689
pISSN - 0960-0833
DOI - 10.1002/(sici)1099-1689(1998090)8:3<113::aid-stvr159>3.0.co;2-8
Subject(s) - parametric statistics , order statistic , parametric model , reliability (semiconductor) , computer science , statistics , nonparametric statistics , econometrics , mathematics , power (physics) , physics , quantum mechanics
This paper addresses a family of probability models for the failure time process known as order statistics models. Conventional order statistics models make rather strong distributional assumptions about the detection times: typically they assume that these come from some parametric family of distributions. In this paper a new model is presented that relaxes these distributional assumptions, and—in the tradition of non‐parametric statistics generally—‘allows the data to speak for themselves’. The accuracy of the new model is compared on some real data sets with the predictions that come from several of the better parametric reliability growth models © 1998 John Wiley & Sons, Ltd.