Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/389
Title: Estimation of P{X < Y} for geometric—exponential model based on complete and censored samples
Authors: Jovanović, Milan 
Affiliations: Probability and Mathematical Statistics 
Keywords: Bayes estimator;Bootstrap confidence interval;Censored data;Exponential distribution;Geometric distribution;Lindley's approximation;Maximum likelihood estimator;Stress–strength;Uniformly minimum variance unbiased estimator
Issue Date: 21-Apr-2017
Journal: Communications in Statistics: Simulation and Computation
Abstract: 
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.
URI: https://research.matf.bg.ac.rs/handle/123456789/389
ISSN: 03610918
DOI: 10.1080/03610918.2015.1073302
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