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Empirical entropy for right censored data

Empirical entropy for right censored data The maximum entropy method has been widely used in many fields, such as statistical mechanics, economics, etc. Its crucial idea is that when we make inference based on partial information, we must use the distribution with maximum entropy subject to whatever is known. In this paper, we investigate the empirical entropy method for right censored data and use simulation to compare the empirical entropy method with the empirical likelihood method. Simulations indicate that the empirical entropy method gives better coverage probability than that of the empirical likelihood method for contaminated and censored lifetime data. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Acta Mathematicae Applicatae Sinica Springer Journals

Empirical entropy for right censored data

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Publisher
Springer Journals
Copyright
Copyright © 2015 by The Editorial Office of AMAS & Springer-Verlag Berlin Heidelberg
Subject
Mathematics; Applications of Mathematics; Math Applications in Computer Science; Theoretical, Mathematical and Computational Physics
ISSN
0168-9673
eISSN
1618-3932
DOI
10.1007/s10255-015-0472-6
Publisher site
See Article on Publisher Site

Abstract

The maximum entropy method has been widely used in many fields, such as statistical mechanics, economics, etc. Its crucial idea is that when we make inference based on partial information, we must use the distribution with maximum entropy subject to whatever is known. In this paper, we investigate the empirical entropy method for right censored data and use simulation to compare the empirical entropy method with the empirical likelihood method. Simulations indicate that the empirical entropy method gives better coverage probability than that of the empirical likelihood method for contaminated and censored lifetime data.

Journal

Acta Mathematicae Applicatae SinicaSpringer Journals

Published: Jun 19, 2015

References