期刊
METRIKA
卷 61, 期 3, 页码 291-308出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s001840400345
关键词
stress-strength model; maximum likelihood estimator; Bayes estimator; bootstrap confidence intervals; Credible intervals; asymptotic distributions
This paper deals with the estimation of P [Y < X] when X and Y are two independent generalized exponential distributions with different shape parameters but having the same scale parameters. The maximum likelihood estimator and its asymptotic distribution is obtained. The asymptotic distribution is used to construct an asymptotic confidence interval of P [Y < X]. Assuming that the common scale parameter is known, the maximum likelihood estimator, uniformly minimum variance unbiased estimator and Bayes estimator of P [Y < X] are obtained. Different confidence intervals are proposed. Monte Carlo simulations are performed to compare the different proposed methods. Analysis of a simulated data set has also been presented for illustrative purposes.
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