Interval Estimation of a P(X1 < X2) Model for Variables having General Inverse Exponential Form Distributions with Unknown Parameters
American Journal of Theoretical and Applied Statistics
Volume 7, Issue 4, July 2018, Pages: 132-138
Received: Feb. 28, 2018;
Accepted: Mar. 26, 2018;
Published: May 3, 2018
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N. A. Mokhlis, Department of Mathematics, Ain Shams University, Cairo, Egypt
E. J. Ibrahim, Department of Mathematics, Ain Shams University, Cairo, Egypt
D. M. Gharieb, Department of Mathematics, Ain Shams University, Cairo, Egypt
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In this article the interval estimation of a P(X1 < X2) model is discussed when X1 and X2are non-negative independent random variables, having general inverse exponential form distributions with different unknown parameters. Different interval estimators are derived, by applying different approaches. A simulation study is performed to compare the estimators obtained. The comparison is carried out on basis of average length, average coverage, and tail errors. The results are illustrated, using inverse Weibull distribution as an example of the general inverse exponential form distribution.
General Inverse Exponential Form Distribution, Coverage Probability, Bootstrap Confidence Interval, Generalized Pivotal Quantity
To cite this article
N. A. Mokhlis,
E. J. Ibrahim,
D. M. Gharieb,
Interval Estimation of a P(X1 < X2) Model for Variables having General Inverse Exponential Form Distributions with Unknown Parameters, American Journal of Theoretical and Applied Statistics.
Vol. 7, No. 4,
2018, pp. 132-138.
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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