NDLI: Estimation of P(Y < X) in Lindley distribution using progressively first failure censoring

Content Provider	Springer Nature Link
Author	Kumar, Kapil Krishna, Hare Garg, Renu
Copyright Year	2014
Abstract	The probability P(Y < X) plays an important role in reliability analysis as it represents reliability in a stress–strength model and availability when Y and X are stress and strength variables, respectively. In reliability theory Lindley distribution has been established as a useful lifetime model and inference procedures for its reliability characteristics are being developed in the literature. To develop these inferences, life testing experiments are conducted which are time consuming and costly in nature. To save time and money various types of censoring plans are used. One such censoring scheme called Progressive censoring has recently become very popular in reliability theory. Progressively first failure censoring is a generalization of progressive censoring scheme and is useful in various practical situations when testing material is inexpensive. In view of above in this paper, maximum likelihood and Bayes estimates for the parameter δ = P(Y < X) are studied when X and Y are Lindley random variables. The data are collected using progressively first failure censoring. A Monte Carlo simulation study is performed to compare different methods of estimation. Two examples, including a real data example, are also given to illustrate the proposed estimates in the paper.
Starting Page	330
Ending Page	341
Page Count	12
File Format	PDF
ISSN	09756809
Journal	International Journal of System Assurance Engineering and Management
Volume Number	6
Issue Number	3
e-ISSN	09764348
Language	English
Publisher	Springer India
Publisher Date	2014-06-08
Publisher Place	New Delhi
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Lindley distribution Progressively first failure censoring Maximum likelihood estimation Confidence interval Bayes estimation Quality Control, Reliability, Safety and Risk Engineering Economics, Organization, Logistics, Marketing
Content Type	Text
Resource Type	Article
Subject	Strategy and Management Safety, Risk, Reliability and Quality

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