Some results envolving the concepts of moment generating function and affinity between distribution functions. Extension for r k-dimensional normal distribution functions [PDF]
, 1999 We present a function ρ (F1, F2, t) which contains Matusita's affinity and expresses the affinity between moment generating functions. An interesting results is expressed through decomposition of this affinity ρ (F1, F2, t) when the functions considered ...
Dorival Campos, A.
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Partial Distance Correlation with Methods for Dissimilarities
, 2014 Distance covariance and distance correlation are scalar coefficients that characterize independence of random vectors in arbitrary dimension. Properties, extensions, and applications of distance correlation have been discussed in the recent literature ...
Rizzo, Maria L., Szekely, Gabor J.
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Detecting independence of random vectors: generalized distance covariance and Gaussian covariance
, 2018 Distance covariance is a quantity to measure the dependence of two random vectors. We show that the original concept introduced and developed by Sz\'{e}kely, Rizzo and Bakirov can be embedded into a more general framework based on symmetric L\'{e}vy ...
Böttcher, Björn +2 more
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Remarks and Open Problems in the Area of the FKG Inequality [PDF]
, 1984 The FKG inequality is an effective device when the requisite assumptions can be verified. Sometimes these have to be approached circuitously. This is discussed with reference to past uses and suggestions for work on the range of applicability.
Joag-Dev, Kumar +2 more
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Another generalization of the bivariate FGM distribution with two-dimensional extensions [PDF]
, 2012 The Farlie–Gumbel–Morgenstern family of bivariate distributions with given marginals is frequently used in theory and applications and has been generalized in many ways.
Cuadras, Carles M., Díaz, Walter
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A measure of mutual complete dependence [PDF]
, 2007 Two random variables X and Y are mutually completely dependent (m.c.d.) if there is a measurable bijection f with P(Y = f(X)) = 1. For continuous X and Y , a natural approach to constructing a measure of dependence is via the distance between the ...
Siburg, Karl Friedrich +1 more
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Archimedean Copulae and Positive Dependence. [PDF]
In the first part of the paper we consider positive dependence properties of Archimedean copulae. Especially we characterize the Archimedean copulae that are multivariate totally positive of order 2 (MTP2) and conditionally increasing in sequence. In the
Alfred Müller, Marco Scarsini
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Negative dependence and the geometry of polynomials
, 2007 We introduce the class of {\em strongly Rayleigh} probability measures by means of geometric properties of their generating polynomials that amount to the stability of the latter.
Borcea, Julius +2 more
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Testing conditional independence using maximal nonlinear conditional correlation
, 2010 In this paper, the maximal nonlinear conditional correlation of two random vectors $X$ and $Y$ given another random vector $Z$, denoted by $\rho_1(X,Y|Z)$, is defined as a measure of conditional association, which satisfies certain desirable properties ...
Huang, Tzee-Ming
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Zonoids, Linear Dependence, and Size-Biased Distributions on the Simplex. [PDF]
The zonoid of a d-dimensional random vector is used as a tool for measuring linear dependence among its components. A preorder of linear dependence is defined through inclusion of the zonoids.
Marco Dall’Aglio, Marco Scarsini
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