Maximizable informational entropy as measure of probabilistic uncertainty
arXiv:0803.3110 · doi:10.1142/S0217979210054713
Abstract
In this work, we consider a recently proposed entropy S (called varentropy) defined by a variational relationship dI=beta*(d<x>-<dx>) as a measure of uncertainty of random variable x. By definition, varentropy underlies a generalized virtual work principle <dx>=0 leading to maximum entropy d(I-beta*<x>)=0. This paper presents an analytical investigation of this maximizable entropy for several distributions such as stretched exponential distribution, kappa-exponential distribution and Cauchy distribution.
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- A counterexample against the Lesche stability of a generic entropy functional
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