Abstract
In this paper, we consider the problem of estimation of \(R=P(X<Y)\), when X and Y are dependent and measurement on one variable is difficult. The maximum likelihood estimate and bayes estimate of R are obtained based on censored data when (X, Y) follows bivariate normal distribution. The confidence intervals for R are also obtained. Monte Carlo simulations are carried out to study the accuracy of the proposed estimators. The inferential procedure developed in this paper is also illustrated using a real data.
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Chacko, M., Mathew, S. Inference on \(P(X<Y)\) for Bivariate Normal Distribution based on Censored Data. J Indian Soc Probab Stat 21, 487–509 (2020). https://doi.org/10.1007/s41096-020-00092-w
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DOI: https://doi.org/10.1007/s41096-020-00092-w