Abstract
In this paper, we discuss the problem of estimating reliability (R) of a component based on maximum likelihood estimators (MLEs). The reliability of a component is given byR=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(BVP) distribution. We obtain an asymptotic normal(AN) distribution of MLE of the reliability(R).
Similar content being viewed by others
References
Beg, M.A. and Singh, N. (1979). Estimation ofP[Y<X] for pareto distribution.IEEE transactions on Reliability, R-28, 411–14.
Enis, P. and Geisser, S. (1971). Estimation of the probability thatY<X.J. Amer. Statist. Assn., 66, 162–68.
Jana, P.K. (1994). Estimation ofP[Y<X] in the bivariate exponential case due to Marshall-Olkin.J. Ind. Statist. Assn., 32, 35–37.
Marshall, A.W. and Olkin, I. (1967). A multivariate exponential distribution.J. Amer. Statist. Assn., 62, 30–44.
Mukherjee, S.P. and Saran, L.K. (1985). Estimation of failure probability from a bivariate normal stress-strength distribution.Microelectonics and Reliability, 25, 692–702.
Veenus, P. and Nair, K.R.M. (1994). Characterization of a bivariate pareto distribution.J. Ind. Statist. Assn., 32, 15–20.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Hanagal, D.D. Note on estimation of reliability under bivariate pareto stress-strength model. Statistical Papers 38, 453–459 (1997). https://doi.org/10.1007/BF02926000
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/BF02926000