Cumulative ratio information based on general cumulative entropy. Issue 3 (11th February 2017)

• Record Type: Journal Article
• Authors: Park, Sangun; Kim, Ilmun
• Is Part Of: Journal of statistical computation and simulation. Volume 87:Issue 3(2017)
• Page Start: 563
• Page End: 576
• Publication Date: 2017-02-11
• Subjects: Goodness-of-fit -- Kullback–Leibler information -- logistic distribution -- maximum entropy -- order statistics; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5028505
• DOI: 10.1080/00949655.2016.1219911
• Languages: English
• ISSNs: 0094-9655

Abstract

ABSTRACT: In this paper, we suggest an extension of the cumulative residual entropy (CRE) and call it generalized cumulative entropy . The proposed entropy not only retains attributes of the existing uncertainty measures but also possesses the absolute homogeneous property with unbounded support, which the CRE does not have. We demonstrate its mathematical properties including the entropy of order statistics and the principle of maximum general cumulative entropy. We also introduce the cumulative ratio information as a measure of discrepancy between two distributions and examine its application to a goodness-of-fit test of the logistic distribution. Simulation study shows that the test statistics based on the cumulative ratio information have comparable statistical power with competing test statistics.