Inference on P(X < Y) for Extreme Values

Sudhansu S. Maiti^1, and Sudhir Murmu²

¹Department of Statistics, Visva-Bharati University Santiniketan, India

²District Rural Development Agency Khunti, Jharkhand, India

Cite this paper

Sudhansu S. Maiti and Sudhir Murmu. Inference on P(X < Y) for Extreme Values. American Journal of Applied Mathematics and Statistics. 2014; 2(3):121-128. doi: 10.12691/AJAMS-2-3-6

Abstract

The article considers the problem of , when X and Y belong to independently distributed two extreme value distributions. Maximum likelihood estimate of R has been found out and the estimates assuming different distributions have been compared for complete samples. Lower confidence limits of R have been found out by Delta method and bootstrap method. The Bayes estimate of R has also been calculated using MCMC approach.

Keywords

Bayes estimate, delta method, Lower Confidence Limit, Metropolis-Hastings algorithm

Copyright

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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