… unbiased estimation of Pr Y < X} under the assumption that X and Y … Y are independent
negative exponential random variables then the minimum variance unbiased estimator of Pr {Y < …

… In this paper we consider the problem of estimating reliability in the stress … , Y has CDF
F2(y). The main aim of this paper is to focus on the inference on R = P(X>Y ), where X and Y are …

… The main aim of this paper is to focus on the inference of R ž P―Y < X , where Y $ GEða; kÞ,
X $ GEðb; kÞ and they are independently distributed. Here the notation $ means ‘follows’ or …

… If we let D denote the data obtained on the basis of a sample of independent observations
from the population specified by f(z, y I Q) and p(Q) be the joint prior distribution of the …

… estimating R=P(Y<X) A general context in which this problem can arise is a reliability study
where X is strength (or supply), Y … The estimation problem is to estimate R = P(Y<X) based on …

… In this paper, we focus on estimation of R = P [ Y < X ] , where X and Y follow the
generalized Pareto (GP) distribution with different parameters. We obtain the MLE of R and its …

This paper provides a simulation study which compares three estimators for R = P(Y<X) when
Y and X are two independent but not identically distributed Burr random variables. These …

… x{ be unbiased estimates of the parameters Y and X based on the i-th sub-sample, (i = 1, 2,
..., n). The following two product estimators can be considered to estimate the parameter Y : …

… This article considers the estimation of R = P(Y < X) when X and Y are distributed as two …
Based on complete X-sample and Y-sample, we would like to draw statistical inference on R…

… It may be mentioned that μ is an over estimate of μ . As has been suggested by … on estimation
of the stress–strength parameter, where μ 1 and μ 2 are the location parameters of X and Y …