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Some properties and applications of cumulative Kullback–Leibler information
Author(s) -
Crescenzo Antonio Di,
Longobardi Maria
Publication year - 2015
Publication title -
applied stochastic models in business and industry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.413
H-Index - 40
eISSN - 1526-4025
pISSN - 1524-1904
DOI - 10.1002/asmb.2116
Subject(s) - kullback–leibler divergence , cumulative distribution function , monotonic function , computer science , measure (data warehouse) , information theory , function (biology) , reliability (semiconductor) , mathematics , statistics , artificial intelligence , data mining , probability density function , mathematical analysis , power (physics) , physics , quantum mechanics , evolutionary biology , biology
The cumulative Kullback–Leibler information has been proposed recently as a suitable extension of Kullback–Leibler information to the cumulative distribution function. In this paper, we obtain various results on such a measure, with reference to its relation with other information measures and notions of reliability theory. We also provide some lower and upper bounds. A dynamic version of the cumulative Kullback–Leibler information is then proposed for past lifetimes. Furthermore, we investigate its monotonicity property, which is related to some new concepts of relative aging. Moreover, we propose an application to the failure of nanocomponents. Finally, in order to provide an application in image analysis, we introduce the empirical cumulative Kullback–Leibler information and prove an asymptotic result. Copyright © 2015 John Wiley & Sons, Ltd.