Results 51 to 60 of about 95 (91)

Fast estimation of Kendall's Tau and conditional Kendall's Tau matrices under structural assumptions

Dependence Modeling
Kendall’s tau and conditional Kendall’s tau matrices are multivariate (conditional) dependence measures between the components of a random vector. For large dimensions, available estimators are computationally expensive and can be improved by averaging ...
van der Spek Rutger, Derumigny Alexis
doaj   +1 more source

Robust Dependence Detection in Official Statistics: A Data Based Methodology

In the domain of offcial statistics, the ability to reliably detect the dependence between socioeconomic indicators is crucial for policy formulation, model validation, and quality control.
STHITADHI DAS
core   +1 more source

The best lower bound of sample correlation coefficient with ordered restriction

In this paper, it is shown that the sample correlation coefficient between two sets of ordered samples x(1) [less-than-or-equals, slant] ... [less-than-or-equals, slant] x(n) and y(1) [less-than-or-equals, slant] ...
Hwang, Tea-Yuan, Hu, Chin-Yuan
core  

Operator trigonometry of multivariate finance

We inquire into an operator-trigonometric analysis of certain multi-asset financial pricing models. Our goal is to provide a new geometric point of view for the understanding and analysis of such financial instruments.
Gustafson, Karl
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Construction of asymmetric multivariate copulas

In this paper we introduce two methods for the construction of asymmetric multivariate copulas. The first is connected with products of copulas. The second approach generalises the Archimedean copulas.
Liebscher, Eckhard
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Optimal discriminant functions for normal populations

A class of discriminant rules which includes Fisher's linear discriminant function and the likelihood ratio criterion is defined. Using asymptotic expansions of the distributions of the discriminant functions in this class, we derive a formula for cut ...
Aoshima, Makoto, Wakaki, Hirofumi
core  

Eigenanalysis on a bivariate covariance kernel

Certain constructions of copulas can be interpreted as an eigendecomposition of a kernel. We study some properties of the eigenfunctions and their integrals of a covariance kernel related to a bivariate distribution.
Cuadras, Carles M., Cuadras, Daniel
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A new dependence ordering with applications

In this paper, we introduce a new copula-based dependence order to compare the relative degree of dependence between two pairs of random variables. Relationship of the new order to the existing dependence orders is investigated.
Kochar, Subhash, Xu, Maochao
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Asymptotic expansions of test statistics for dimensionality and additional information in canonical correlation analysis when the dimension is large

This paper examines asymptotic expansions of test statistics for dimensionality and additional information in canonical correlation analysis based on a sample of size N=n+1 on two sets of variables, i.e., and .
Sakurai, Tetsuro
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Generalized covariance inequalities

Open Mathematics, 2011
Matuła Przemysław, Ziemba Maciej
doaj   +1 more source