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Multi-variate correlation and mixtures of product measures

Tim Austin (2020)

Kybernetika

Total correlation (‘TC’) and dual total correlation (‘DTC’) are two classical ways to quantify the correlation among an n -tuple of random variables. They both reduce to mutual information when n = 2 . The first part of this paper sets up the theory of TC and DTC for general random variables, not necessarily finite-valued. This generality has not been exposed in the literature before. The second part considers the structural implications when a joint distribution μ has small TC or DTC. If TC ( μ ) = o ( n ) , then μ is...

New estimates and tests of independence in semiparametric copula models

Salim Bouzebda, Amor Keziou (2010)

Kybernetika

We introduce new estimates and tests of independence in copula models with unknown margins using φ -divergences and the duality technique. The asymptotic laws of the estimates and the test statistics are established both when the parameter is an interior or a boundary value of the parameter space. Simulation results show that the choice of χ 2 -divergence has good properties in terms of efficiency-robustness.

Notion of information and independent component analysis

Una Radojičić, Klaus Nordhausen, Hannu Oja (2020)

Applications of Mathematics

Partial orderings and measures of information for continuous univariate random variables with special roles of Gaussian and uniform distributions are discussed. The information measures and measures of non-Gaussianity including the third and fourth cumulants are generally used as projection indices in the projection pursuit approach for the independent component analysis. The connections between information, non-Gaussianity and statistical independence in the context of independent component analysis...

Nuevas medidas de información paramétricas reales basadas en la matriz de Fisher.

Agustín Turrero Nogués (1989)

Trabajos de Estadística

Se proponen en este trabajo nuevos funcionales reales de la matriz de información de Fisher como medidas de información paramétricas. Se analizan las propiedades de dichas medidas. Se presenta un método sencillo, basado en la matriz de Fisher, para obtener medidas de información paramétricas reales con la propiedad de invariancia bajo transformaciones biyectivas del espacio paramétrico.

Number of hidden states and memory: a joint order estimation problem for Markov chains with Markov regime

Antoine Chambaz, Catherine Matias (2009)

ESAIM: Probability and Statistics

This paper deals with order identification for Markov chains with Markov regime (MCMR) in the context of finite alphabets. We define the joint order of a MCMR process in terms of the number k of states of the hidden Markov chain and the memory m of the conditional Markov chain. We study the properties of penalized maximum likelihood estimators for the unknown order (k, m) of an observed MCMR process, relying on information theoretic arguments. The novelty of our work relies in the joint...

Objective Bayesian point and region estimation in location-scale models.

José M. Bernardo (2007)

SORT

Point and region estimation may both be described as specific decision problems. In point estimation, the action space is the set of possible values of the quantity on interest; in region estimation, the action space is the set of its possible credible regions. Foundations dictate that the solution to these decision problems must depend on both the utility function and the prior distribution. Estimators intended for general use should surely be invariant under one-to-one transformations, and this...

On generalized conditional cumulative past inaccuracy measure

Amit Ghosh, Chanchal Kundu (2018)

Applications of Mathematics

The notion of cumulative past inaccuracy (CPI) measure has recently been proposed in the literature as a generalization of cumulative past entropy (CPE) in univariate as well as bivariate setup. In this paper, we introduce the notion of CPI of order α and study the proposed measure for conditionally specified models of two components failed at different time instants, called generalized conditional CPI (GCCPI). Several properties, including the effect of monotone transformation and bounds of GCCPI...

On generalized information and divergence measures and their applications: a brief review.

Inder Jeet Taneja, Leandro Pardo, Domingo Morales, María Luisa Menéndez (1989)

Qüestiió

The aim of this review is to give different two-parametric generalizations of the following measures: directed divergence (Kullback and Leibler, 1951), Jensen difference divergence (Burbea and Rao 1982 a,b; Rao, 1982) and Jeffreys invariant divergence (Jeffreys, 1946). These generalizations are put in the unified expression and their properties are studied. The applications of generalized information and divergence measures to comparison of experiments and the connections with Fisher information...

On limiting towards the boundaries of exponential families

František Matúš (2015)

Kybernetika

This work studies the standard exponential families of probability measures on Euclidean spaces that have finite supports. In such a family parameterized by means, the mean is supposed to move along a segment inside the convex support towards an endpoint on the boundary of the support. Limit behavior of several quantities related to the exponential family is described explicitly. In particular, the variance functions and information divergences are studied around the boundary.

On metric divergences of probability measures

Igor Vajda (2009)

Kybernetika

Standard properties of φ -divergences of probability measures are widely applied in various areas of information processing. Among the desirable supplementary properties facilitating employment of mathematical methods is the metricity of φ -divergences, or the metricity of their powers. This paper extends the previously known family of φ -divergences with these properties. The extension consists of a continuum of φ -divergences which are squared metric distances and which are mostly new but include...

On the amount of information resulting from empirical and theoretical knowledge.

Igor Vajda, Arnost Vesely, Jana Zvarova (2005)

Revista Matemática Complutense

We present a mathematical model allowing formally define the concepts of empirical and theoretical knowledge. The model consists of a finite set P of predicates and a probability space (Ω, S, P) over a finite set Ω called ontology which consists of objects ω for which the predicates π ∈ P are either valid (π(ω) = 1) or not valid (π(ω) = 0). Since this is a first step in this area, our approach is as simple as possible, but still nontrivial, as it is demonstrated by examples. More realistic approach...

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