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Expansions for Repeated Integrals of Products with Applications to the Multivariate Normal

Christopher S. Withers, Saralees Nadarajah (2011)

ESAIM: Probability and Statistics

We extend Leibniz' rule for repeated derivatives of a product to multivariate integrals of a product. As an application we obtain expansions for P(a < Y < b) for Y ~ Np(0,V) and for repeated integrals of the density of Y. When V−1y > 0 in R3 the expansion for P(Y < y) reduces to one given by [H. Ruben J. Res. Nat. Bureau Stand. B 68 (1964) 3–11]. in terms of the moments of Np(0,V−1). This is shown to be a special case of an expansion in terms of the multivariate Hermite...

Extreme distribution functions of copulas

Manuel Úbeda-Flores (2008)

Kybernetika

In this paper we study some properties of the distribution function of the random variable C(X,Y) when the copula of the random pair (X,Y) is M (respectively, W) – the copula for which each of X and Y is almost surely an increasing (respectively, decreasing) function of the other –, and C is any copula. We also study the distribution functions of M(X,Y) and W(X,Y) given that the joint distribution function of the random variables X and Y is any copula.

Generación de un sistema bivariante con marginales dadas y estimación de su parámetro de dependencia.

Jordi Ocaña, Carles Maria Cuadras (1987)

Qüestiió

En este trabajo se proponen dos posibles estimadores del parámetro de dependencia de una familia de distribuciones bivariantes con marginales dadas y se realiza un estudio de Monte Carlo de sus respectivos sesgo y eficiencia, a fin de determinar cuál de ambos estimadores es preferible. También se propone y se estudia, de forma similar, una posible versión "Jackknife" del mejor de los dos estimadores anteriores. En este estudio se emplean técnicas de reducción de la varianza. Para poder realizar...

Generalized logistic model and its orthant tail dependence

Helena Ferreira, Luisa Pereira (2011)

Kybernetika

The Multivariate Extreme Value distributions have shown their usefulness in environmental studies, financial and insurance mathematics. The Logistic or Gumbel-Hougaard distribution is one of the oldest multivariate extreme value models and it has been extended to asymmetric models. In this paper we introduce generalized logistic multivariate distributions. Our tools are mixtures of copulas and stable mixing variables, extending approaches in Tawn [14], Joe and Hu [6] and Fougères et al. [3]. The...

Geometric infinite divisibility, stability, and self-similarity: an overview

Tomasz J. Kozubowski (2010)

Banach Center Publications

The concepts of geometric infinite divisibility and stability extend the classical properties of infinite divisibility and stability to geometric convolutions. In this setting, a random variable X is geometrically infinitely divisible if it can be expressed as a random sum of N p components for each p ∈ (0,1), where N p is a geometric random variable with mean 1/p, independent of the components. If the components have the same distribution as that of a rescaled X, then X is (strictly) geometric stable....

How non-symmetric can a copula be?

Erich Peter Klement, Radko Mesiar (2006)

Commentationes Mathematicae Universitatis Carolinae

A two-place function measuring the degree of non-symmetry for (quasi-)copulas is considered. We construct copulas which are maximally non-symmetric on certain subsets of the unit square. It is shown that there is no copula (and no quasi-copula) which is maximally non-symmetric on the whole unit square.

Jacobians of certain transformations of singular matrices

José A. Díaz-García, Ramón Gutiérrez-Jáimez (2009)

Applicationes Mathematicae

In this study various Jacobians of transformations of singular random matrices are found. An alternative proof of Uhlig's first conjecture (Uhlig (1994)) is proposed. Furthermore, we propose various extensions of this conjecture under different singularities. Finally, an application of the theory of singular distributions is discussed.

Markov bases of conditional independence models for permutations

Villő Csiszár (2009)

Kybernetika

The L-decomposable and the bi-decomposable models are two families of distributions on the set S n of all permutations of the first n positive integers. Both of these models are characterized by collections of conditional independence relations. We first compute a Markov basis for the L-decomposable model, then give partial results about the Markov basis of the bi-decomposable model. Using these Markov bases, we show that not all bi-decomposable distributions can be approximated arbitrarily well by...

Markov operators and n-copulas

P. Mikusiński, M. D. Taylor (2009)

Annales Polonici Mathematici

We extend the definition of Markov operator in the sense of J. R. Brown and of earlier work of the authors to a setting appropriate to the study of n-copulas. Basic properties of this extension are studied.

Modeling biased information seeking with second order probability distributions

Gernot D. Kleiter (2015)

Kybernetika

Updating probabilities by information from only one hypothesis and thereby ignoring alternative hypotheses, is not only biased but leads to progressively imprecise conclusions. In psychology this phenomenon was studied in experiments with the “pseudodiagnosticity task”. In probability logic the phenomenon that additional premises increase the imprecision of a conclusion is known as “degradation”. The present contribution investigates degradation in the context of second order probability distributions....

Modelling financial time series using reflections of copulas

Jozef Komorník, Magda Komorníková (2013)

Kybernetika

We have intensified studies of reflections of copulas (that we introduced recently in [6]) and found that their convex combinations exhibit potentially useful fitting properties for original copulas of the Normal, Frank, Clayton and Gumbel types. We show that these properties enable us to construct interesting models for the relations between investment in stocks and gold.

Multiplicative Cauchy functional equation and the equation of ratios on the Lorentz cone

Jacek Wesołowski (2007)

Studia Mathematica

It is proved that the solution of the multiplicative Cauchy functional equation on the Lorentz cone of dimension greater than two is a power function of the determinant. The equation is solved in full generality, i.e. no smoothness assumptions on the unknown function are imposed. Also the functional equation of ratios, of a similar nature, is solved in full generality.

Multivariate Extreme Value Theory - A Tutorial with Applications to Hydrology and Meteorology

Anne Dutfoy, Sylvie Parey, Nicolas Roche (2014)

Dependence Modeling

In this paper, we provide a tutorial on multivariate extreme value methods which allows to estimate the risk associated with rare events occurring jointly. We draw particular attention to issues related to extremal dependence and we insist on the asymptotic independence feature. We apply the multivariate extreme value theory on two data sets related to hydrology and meteorology: first, the joint flooding of two rivers, which puts at risk the facilities lying downstream the confluence; then the joint...

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