Estimation of P{X < Y} for geometric-exponential model based on complete and censored samples

被引:15
作者
Jovanovic, Milan [1 ]
机构
[1] Univ Belgrade, Fac Math, Belgrade, Serbia
关键词
Bayes estimator; Bootstrap confidence interval; Censored data; Exponential distribution; Geometric distribution; Lindley's approximation; Maximum likelihood estimator; Stress-strength; Uniformly minimum variance unbiased estimator; STRESS-STRENGTH RELIABILITY; WEIBULL DISTRIBUTION; P(Y-LESS-THAN-X); P(X-LESS-THAN-Y); DISTRIBUTIONS; PARAMETER; INFERENCE; X);
D O I
10.1080/03610918.2015.1073302
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
This article deals with the estimation of R = P{X < Y}, where X and Y are independent random variables from geometric and exponential distribution, respectively. For complete samples, the MLE of R, its asymptotic distribution, and confidence interval based on it are obtained. The procedure for deriving bootstrap-p confidence interval is presented. The UMVUE of R and UMVUE of its variance are derived. The Bayes estimator of R is investigated and its Lindley's approximation is obtained. A simulation study is performed in order to compare these estimators. Finally, all point estimators for right censored sample from the exponential distribution, are obtained.
引用
收藏
页码:3050 / 3066
页数:17
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