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Convexity inequalities for estimating generalized conditional entropies from below

Alexey E. Rastegin (2012)

Kybernetika

Generalized entropic functionals are in an active area of research. Hence lower and upper bounds on these functionals are of interest. Lower bounds for estimating Rényi conditional α -entropy and two kinds of non-extensive conditional α -entropy are obtained. These bounds are expressed in terms of error probability of the standard decision and extend the inequalities known for the regular conditional entropy. The presented inequalities are mainly based on the convexity of some functions. In a certain...

Copula approach to residuals of regime-switching models

Anna Petričková, Magda Komorníková (2012)

Kybernetika

The autocorrelation function describing the linear dependence is not suitable for description of residual dependence of the regime-switching models. In this contribution, inspired by Rakonczai ([20]), we will model the residual dependence of the regime-switching models (SETAR, LSTAR and ESTAR) with the autocopulas (Archimedean, EV and their convex combinations) and construct improved quality models for the original real time series.

Copula-based dependence measures

Eckhard Liebscher (2014)

Dependence Modeling

The aim of the present paper is to examine two wide classes of dependence coefficients including several well-known coefficients, for example Spearman’s ρ, Spearman’s footrule, and the Gini coefficient. There is a close relationship between the two classes: The second class is obtained by a symmetrisation of the coefficients in the former class. The coefficients of the first class describe the deviation from monotonically increasing dependence. The construction of the coefficients can be explained...

Copula-based grouped risk aggregation under mixed operation

Quan Zhou, Zhenlong Chen, Ruixing Ming (2016)

Applications of Mathematics

This paper deals with the problem of risk measurement under mixed operation. For this purpose, we divide the basic risks into several groups based on the actual situation. First, we calculate the bounds for the subsum of every group of basic risks, then we obtain the bounds for the total sum of all the basic risks. For the dependency relationships between the basic risks in every group and all of the subsums, we give different copulas to describe them. The bounds for the aggregated risk under mixed...

Copula–Induced Measures of Concordance

Sebastian Fuchs (2016)

Dependence Modeling

We study measures of concordance for multivariate copulas and copulas that induce measures of concordance. To this end, for a copula A, we consider the maps C → R given by [...] where C denotes the collection of all d–dimensional copulas, M is the Fréchet–Hoeffding upper bound, Π is the product copula, [. , .] : C × C → R is the biconvex form given by [C, D] := ∫ [0,1]d C(u) dQD(u) with the probability measure QD associated with the copula D, and ψΛ C → C is a transformation of copulas. We present...

Copulas with given values on a horizontal and a vertical section

Fabrizio Durante, Anna Kolesárová, Radko Mesiar, Carlo Sempi (2007)

Kybernetika

In this paper we study the set of copulas for which both a horizontal section and a vertical section have been given. We give a general construction for copulas of this type and we provide the lower and upper copulas with these sections. Symmetric copulas with given horizontal section are also discussed, as well as copulas defined on a grid of the unit square. Several examples are presented.

Core functions and core divergences of regular distributions

Zdeněk Fabián, Igor Vajda (2003)

Kybernetika

On bounded or unbounded intervals of the real line, we introduce classes of regular statistical families, called Johnson families because they are obtained using generalized Johnson transforms. We study in a rigorous manner the formerly introduced concept of core function of a distribution from a Johnson family, which is a modification of the well known score function and which in a one-to-one manner represents the distribution. Further, we study Johnson parametrized families obtained by Johnson...

Corrélation entre variables nominales, ordinales, métriques ou numériques

Éric Térouanne (1998)

Mathématiques et Sciences Humaines

Un coefficient de corrélation est défini pour la distribution empirique conjointe de deux variables statistiques, que la structure a priori de chacune d'elles soit nominale, ordinale, métrique ou numérique. L'obtention d'un formalisme commun à toutes ces structures permet d'affiner l'analyse de la liaison entre les variables, en termes d'homogénéité (variables ordonnées), d'ordres sous-jacents (variables non-ordonnées) ou d'ordre induit (cas mixte).

Correlation-based feature selection strategy in classification problems

Krzysztof Michalak, Halina Kwaśnicka (2006)

International Journal of Applied Mathematics and Computer Science

In classification problems, the issue of high dimensionality, of data is often considered important. To lower data dimensionality, feature selection methods are often employed. To select a set of features that will span a representation space that is as good as possible for the classification task, one must take into consideration possible interdependencies between the features. As a trade-off between the complexity of the selection process and the quality of the selected feature set, a pairwise...

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