This paper addresses the following question: How much information do the kernel function and the bandwidth provide for nonparametric kernel estimation? The question is addressed by showing that kernel estimation of a cumulative distribution function (CDF) is an information transmission procedure...

Which component is most important for a system's survival? We answer this question by ranking the information relationship between a system and its components. The mutual information (M) measures dependence between the operational states of the system and a component for a mission time as well...

This paper first illustrates that a mutual information index detects and ranks dependence of a wide variety of absolutely continuous families, but the popular association and variance reduction indices fail to serve as such “common metrics”. We then elaborate on some theoretical merits of...

This paper shows that multivariate distributions can be characterized as maximum entropy (ME) models based on the well-known general representation of density function of the ME distribution subject to moment constraints. In this approach, the problem of ME characterization simplifies to the...

We consider the class of multivariate distributions that gives the distribution of the sum of uncorrelated random variables by the product of their marginal distributions. This class is defined by a representation of the assumption of sub-independence, formulated previously in terms of the...

In many reliability and survival analysis problems the current age of an item under study must be taken into account by information measures of the lifetime distribution. Kullback-Leibler information and Shannon entropy have been considered in this context, which led to information measures that...