Shrinkage estimation of P(Y<X) in the exponential case

We consider the problem of estimating R = P(Y < X),where X and Y have independent exponential distributions with parameters theta and lambda respectively. Assuming that there is a prior guess or estimate R-0, we develop various shrinkage estimators of R that incorporate this prior information. The performance of the new estimators is investigated and compared with the maximum likelihood estimator using Monte Carlo methods. It is found that some of these estimators are very successful in taking advantage of the prior estimate available. Recommendations concerning the use of these estimators are presented.