Add to ORKGInternational audienceWe introduce a new measure of dependence between the components of a symmetric α-stable random vector. We show that this coefficient satisfies the properties of the classical Pearson coefficient. Moreover, we show that in the case of sub-Gaussian random vectors, this coefficient coincide with the association parameter and the generalized association parameter
In the correlation model, the classical coefficient of multiple determination 2 is a measure of asso...
To quantify the dependence between two random vectors of possibly different dimensions, we propose t...
In this paper we investigate the dependence structure for PARMA models (i.e. ARMA models with period...
International audienceWe introduce a new measure of dependence between the components of a symmetric...
Accepté à Communications in Statistics - Theory and methodsInternational audienceIn this paper we st...
Accepté à Communications in Statistics - Theory and methodsInternational audienceIn this paper we st...
International audienceThe covariation is one of the possible dependence measures for variables where...
In this paper, we discuss a generalized dependence measure which is designed to measure dependence o...
In this paper, we discuss a generalized dependence measure which is designed to measure dependence o...
International audienceThe covariation is one of the possible dependence measures for variables where...
Gaussian copulas are handy tool in many applications. However, when dimension of data is large, ther...
Gaussian copulas are handy tool in many applications. However, when dimension of data is large, ther...
The simple correlation coefficient between two variables has been generalized to measures of associa...
To quantify the dependence between two random vectors of possibly different dimensions, we propose t...
We proposed a new statistical dependency measure called Copula Dependency Coefficient(CDC) for two s...
In the correlation model, the classical coefficient of multiple determination 2 is a measure of asso...
To quantify the dependence between two random vectors of possibly different dimensions, we propose t...
In this paper we investigate the dependence structure for PARMA models (i.e. ARMA models with period...
International audienceWe introduce a new measure of dependence between the components of a symmetric...
Accepté à Communications in Statistics - Theory and methodsInternational audienceIn this paper we st...
Accepté à Communications in Statistics - Theory and methodsInternational audienceIn this paper we st...
International audienceThe covariation is one of the possible dependence measures for variables where...
In this paper, we discuss a generalized dependence measure which is designed to measure dependence o...
In this paper, we discuss a generalized dependence measure which is designed to measure dependence o...
International audienceThe covariation is one of the possible dependence measures for variables where...
Gaussian copulas are handy tool in many applications. However, when dimension of data is large, ther...
Gaussian copulas are handy tool in many applications. However, when dimension of data is large, ther...
The simple correlation coefficient between two variables has been generalized to measures of associa...
To quantify the dependence between two random vectors of possibly different dimensions, we propose t...
We proposed a new statistical dependency measure called Copula Dependency Coefficient(CDC) for two s...
In the correlation model, the classical coefficient of multiple determination 2 is a measure of asso...
To quantify the dependence between two random vectors of possibly different dimensions, we propose t...
In this paper we investigate the dependence structure for PARMA models (i.e. ARMA models with period...