Estimation of P{X ≤ Y} for geometric-Poisson model
In this paper we estimate R=P{X≤Y} when X and Y are independent random variables from geometric and Poisson distribution
respectively. We find maximum likelihood estimator of R and its asymptotic distribution. This asymptotic distribution is used to construct
asymptotic confidence intervals. A procedure for deriving bootstrap
confidence intervals is presented. UMVUE of R and UMVUE of its
variance are derived and also the Bayes estimator of R for conjugate
prior distributions is obtained. Finally, we perform a simulation study
in order to compare these estimators.