This paper considers the use of local '-divergence measures between posterior distribtions under diierent classes of perturbations in order to investigate the inherent robustness of those classes. The smaller value of the limiting local '-divergence implies more robustness for the prior or the likelihood. Two kinds of perturbations(prior and likelihood) are considered for the local sensitivity ...

This paper deals with detection of flooding attacks which are the most common type of Denial of Service (DoS) attacks in a Mobile Agent World. We propose a new framework for the detection of flooding attacks by integrating Divergence measures over Sketch data structure. The performance of the proposed framework is investigated in terms of detection probability and false alarm ratio. We focus on...

In an earlier study, Swain et al. reported on two statistical separability measures which for multiclass feature selection were shown experimentally to be more reliable than divergence. However, the empirical results of that study together with the best theoretical results in the literature left open some practical questions regarding the quantitative characterization of these separability meas...

We discuss a special class of generalized divergence measures by the use of generator functions. Any divergence measure in the class is separated into the difference between cross and diagonal entropy. The diagonal entropy measure in the class associates with a model of maximum entropy distributions; the divergence measure leads to statistical estimation via minimization, for arbitrarily giving...

Inequality indices (i) evaluate the divergence between the income distribution and the hypothetical situation where all individuals have the mean income and (ii) are unambiguously reduced by a Pigou-Dalton progressive transfer. This paper proposes a new approach to evaluate the divergence between any two income distributions, where the second one can be a reference distribution for the first. I...

Estimating word co-occurrence probabilities is a problem underlying many applications in statistical natural language processing. Distance-weighted (or similarityweighted) averaging has been shown to be a promising approach to the analysis of novel co-occurrences. Many measures of distributional similarity have been proposed for use in the distance-weighted averaging framework; here, we empiric...

There are many applications that benefit from computing the exact divergence between 2 discrete probability measures, including machine learning. Unfortunately, in absence of any assumptions on structure or independencies within these distributions, them is an intractable problem high dimensions. We show we able to compute a wide family functionals and divergences, such as alpha-beta divergence...

Cultural divergence is incongruity in the values, attitudes and behaviors among different generations of a society. Identifying factors related to cultural divergence in the social values ​​of parents and children is one of the most important issues in Iranian society, which has been investigated in the present research through a quantitative approach. The statistical population of the study co...

In this paper we introduce the concepts of p−logarithmic and α−power divergence measures and point out a number of basic results.