Note on estimation of reliability under bivariate Pareto stress-strength model. (English) Zbl 0911.62091
Summary: We discuss the problem of estimating reliability \((R)\) of a component based on maximum likelihood estimators (MLEs). The reliability of a component is given by \(R= P[Y< X]\). Here \(X\) is a random strength of a component subjected to a random stress \((Y)\) and \((X,Y)\) follow a bivariate Pareto distribution. We obtain an asymptotic normal (AN) distribution of MLE of the reliability \((R)\).
Keywords:
stress-strength model; asymptotic normality; maximum likelihood estimators; reliability; bivariate Pareto distributionReferences:
[1] | Beg, M. A.; Singh, N., Estimation ofP[Y<X] for pareto distribution, IEEE transactions on Reliability, R-, 28, 411-14 (1979) · Zbl 0418.62083 · doi:10.1109/TR.1979.5220665 |
[2] | Enis, P.; Geisser, S., Estimation of the probability thatY<X, J. Amer. Statist. Assn., 66, 162-68 (1971) · Zbl 0236.62009 · doi:10.2307/2284867 |
[3] | Jana, P. K., Estimation ofP[Y<X] in the bivariate exponential case due to Marshall-Olkin, J. Ind. Statist. Assn., 32, 35-37 (1994) |
[4] | Marshall, A. W.; Olkin, I., A multivariate exponential distribution, J. Amer. Statist. Assn., 62, 30-44 (1967) · Zbl 0147.38106 · doi:10.2307/2282907 |
[5] | Mukherjee, S. P.; Saran, L. K., Estimation of failure probability from a bivariate normal stress-strength distribution, Microelectonics and Reliability, 25, 692-702 (1985) |
[6] | Veenus, P.; Nair, K. R.M., Characterization of a bivariate pareto distribution, J. Ind. Statist. Assn., 32, 15-20 (1994) |
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