AbstractNecessary and sufficient conditions are presented for jointly symmetric stable random vectors to be independent and for a regression involving symmetric stable random variables to be linear. The notion of n-fold dependence is introduced for symmetric stable random variables, and under this condition we determine all monomials in such random variables for which moments exist
This paper deals with multivariate stable distributions. [6], 444-462]. We present counter-examples ...
AbstractSeveral characterizations of multivariate stable distribution are given based on identically...
International audienceWe introduce a new measure of dependence between the components of a symmetric...
AbstractNecessary and sufficient conditions are presented for jointly symmetric stable random vector...
AbstractMultivariate symmetric stable characteristic functions and their properties, as well as cond...
Multivariate symmetric stable characteristic functions and their properties, as well as conditions f...
AbstractThis paper is devoted to the theory and application of multidimensional stable distributions...
International audienceThe covariation is one of the possible dependence measures for variables where...
AbstractMultivariate symmetric stable characteristic functions and their properties, as well as cond...
International audienceThe covariation is one of the possible dependence measures for variables where...
AbstractThis paper is devoted to the theory and application of multidimensional stable distributions...
It is known that each symmetric stable distribution in is related to a norm on that makes embeddable...
A characterization theorem for symmetric stable processes is proved, extending earlier results of Lu...
AbstractSeveral characterizations of multivariate stable distribution are given based on identically...
AbstractJointly α-stable random variables with index 0 < α < 2 have only finite moments of order les...
This paper deals with multivariate stable distributions. [6], 444-462]. We present counter-examples ...
AbstractSeveral characterizations of multivariate stable distribution are given based on identically...
International audienceWe introduce a new measure of dependence between the components of a symmetric...
AbstractNecessary and sufficient conditions are presented for jointly symmetric stable random vector...
AbstractMultivariate symmetric stable characteristic functions and their properties, as well as cond...
Multivariate symmetric stable characteristic functions and their properties, as well as conditions f...
AbstractThis paper is devoted to the theory and application of multidimensional stable distributions...
International audienceThe covariation is one of the possible dependence measures for variables where...
AbstractMultivariate symmetric stable characteristic functions and their properties, as well as cond...
International audienceThe covariation is one of the possible dependence measures for variables where...
AbstractThis paper is devoted to the theory and application of multidimensional stable distributions...
It is known that each symmetric stable distribution in is related to a norm on that makes embeddable...
A characterization theorem for symmetric stable processes is proved, extending earlier results of Lu...
AbstractSeveral characterizations of multivariate stable distribution are given based on identically...
AbstractJointly α-stable random variables with index 0 < α < 2 have only finite moments of order les...
This paper deals with multivariate stable distributions. [6], 444-462]. We present counter-examples ...
AbstractSeveral characterizations of multivariate stable distribution are given based on identically...
International audienceWe introduce a new measure of dependence between the components of a symmetric...
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