Prediction and reconstruction of future and missing unobservable modified Weibull lifetime based on generalized order statistics
Aly, A. (2016). Prediction and reconstruction of future and missing unobservable modified Weibull lifetime based on generalized order statistics. EKB Journal Management System, 24(2), 309-318. doi: 10.1016/j.joems.2015.04.002
Amany E. Aly. "Prediction and reconstruction of future and missing unobservable modified Weibull lifetime based on generalized order statistics". EKB Journal Management System, 24, 2, 2016, 309-318. doi: 10.1016/j.joems.2015.04.002
Aly, A. (2016). 'Prediction and reconstruction of future and missing unobservable modified Weibull lifetime based on generalized order statistics', EKB Journal Management System, 24(2), pp. 309-318. doi: 10.1016/j.joems.2015.04.002
Aly, A. Prediction and reconstruction of future and missing unobservable modified Weibull lifetime based on generalized order statistics. EKB Journal Management System, 2016; 24(2): 309-318. doi: 10.1016/j.joems.2015.04.002

Prediction and reconstruction of future and missing unobservable modified Weibull lifetime based on generalized order statistics

Journal of the Egyptian Mathematical Society
Volume 24, Issue 2, 2016, Page 309-318  XML PDF (424.06 K)
DOI: 10.1016/j.joems.2015.04.002
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Author
Amany E. Aly1, 2
1Department of Mathematics, Faculty of Science, Taibah University, Madinah, Saudi Arabia
2Permanent address: Department of Mathematics, Faculty of Science, Helwan University, Ain Helwan, Cairo, Egypt
Abstract
When a system consisting of independent components of the same type, some appro-
priate actions may be done as soon as a portion of them have failed. It is, therefore, important to
be able to predict later failure times from earlier ones. One of the well-known failure distributions
commonly used to model component life, is the modified Weibull distribution ( MWD ). In this paper,
two pivotal quantities are proposed to construct prediction intervals for future unobservable lifetimes
based on generalized order statistics (gos) from MWD . Moreover, a pivotal quantity is developed to
reconstruct missing observations at the beginning of experiment. Furthermore, Monte Carlo simula-
tion studies are conducted and numerical computations are carried out to investigate the efficiency of
presented results. Finally, two illustrative examples for real data sets are analyzed
Keywords
Modified Weibull distribution; Generalized order statistics; Pivotal quantities; Predicative interval; Probability coverage; Monte Carlo Simulation
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