Let X and Y be independent exponentially distributed random variables having parameters λ and μ respectively. Sharp boundsfor the first two moments of the maximum likelihood estimator and minimum variance unbiased estimator of P(X > Y) are obtained, when μ is known, say 1. When μ is unknown, sharp bounds for the first two moments of the maximum likelihood estimator of p(X > Y) are obtained and a lower bound for the variance of the minimum variance unbiased estimator is also obtained.
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Sathe et al. (1981) studied this question.
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