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On the Mean Residual Life Function and Stress and Strength Analysis under Different Loss Function for Lindley Distribution
Author(s) -
Sajid Ali
Publication year - 2013
Publication title -
journal of quality and reliability engineering
Language(s) - English
Resource type - Journals
eISSN - 2314-8047
pISSN - 2314-8055
DOI - 10.1155/2013/190437
Subject(s) - reliability (semiconductor) , statistics , bayesian probability , prior probability , mathematics , bayes' theorem , exponential distribution , bayes estimator , exponential function , residual , function (biology) , reliability theory , econometrics , algorithm , failure rate , mathematical analysis , power (physics) , physics , quantum mechanics , evolutionary biology , biology
Purpose. Mathematical properties of Lindley distribution are derived under different loss functions. These properties include mean residual life function, Lorenz curve, stress and strength characteristic, and their respective posterior risk via simulation scheme. Methodology. Bayesian approach is used for the reliability characteristics. Results are compared on the basis of posterior risk. Findings. Using prior information on the parameter of Lindley distribution, Bayes estimates for reliability characteristics are compared under different loss functions. Practical Implications. Since Lindley distribution is a mixture of gamma and exponential distribution, so Bayesian estimation of reliability characteristics will have a great implication in reliability theory. Originality. A real life application to waiting time data at the bank is also described for the developed procedures. This study is usefulfor researcher and practitioner in reliability theory

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