summary:On bounded or unbounded intervals of the real line, we introduce classes of regular statistical families, called Johnson families because they are obtained using generalized Johnson transforms. We study in a rigorous manner the formerly introduced concept of core function of a distribution from a Johnson family, which is a modification of the well known score function and which in a one-to-one manner represents the distribution. Further, we study Johnson parametrized families obtained by Johnson transforms of location and scale families, where the location is replaced by a new parameter called Johnson location. We show that Johnson parametrized families contain many important statistical models. One form appropriately normalized $L_...
International audienceThis paper is devoted to the study of the parametric family of multivari- ate ...
Abstract We define two new flexible families of continuous distributions to fit real data by compoun...
Divergence measures are widely used in various applications of pattern recognition, signal processin...
summary:On bounded or unbounded intervals of the real line, we introduce classes of regular statisti...
summary:We propose a simple method of construction of new families of $\phi$%-divergences. This meth...
summary:This paper deals with four types of point estimators based on minimization of information-th...
The Jensen-Shannon divergence is a renown bounded symmetrization of the unbounded Kullback-Leibler d...
summary:We establish a decomposition of the Jensen-Shannon divergence into a linear combination of a...
AbstractIn statistical estimation problems measures between probability distributions play significa...
AbstractLetZ1, …, Znbe a random sample of sizen⩾2 from ad-variate continuous distribution functionH,...
Let Z1,..., Zn be a random sample of size n2 from a d-variate continuous distribution function H, an...
summary:In this paper, we are mainly concerned with characterizing matrices that map every bounded s...
We describe a framework to build distances by measuring the tightness of inequalities and introduce ...
We introduce and study general mathematical properties of a new generator of continuous distribution...
This thesis documents three different contributions in statistical learning theory. They were develo...
International audienceThis paper is devoted to the study of the parametric family of multivari- ate ...
Abstract We define two new flexible families of continuous distributions to fit real data by compoun...
Divergence measures are widely used in various applications of pattern recognition, signal processin...
summary:On bounded or unbounded intervals of the real line, we introduce classes of regular statisti...
summary:We propose a simple method of construction of new families of $\phi$%-divergences. This meth...
summary:This paper deals with four types of point estimators based on minimization of information-th...
The Jensen-Shannon divergence is a renown bounded symmetrization of the unbounded Kullback-Leibler d...
summary:We establish a decomposition of the Jensen-Shannon divergence into a linear combination of a...
AbstractIn statistical estimation problems measures between probability distributions play significa...
AbstractLetZ1, …, Znbe a random sample of sizen⩾2 from ad-variate continuous distribution functionH,...
Let Z1,..., Zn be a random sample of size n2 from a d-variate continuous distribution function H, an...
summary:In this paper, we are mainly concerned with characterizing matrices that map every bounded s...
We describe a framework to build distances by measuring the tightness of inequalities and introduce ...
We introduce and study general mathematical properties of a new generator of continuous distribution...
This thesis documents three different contributions in statistical learning theory. They were develo...
International audienceThis paper is devoted to the study of the parametric family of multivari- ate ...
Abstract We define two new flexible families of continuous distributions to fit real data by compoun...
Divergence measures are widely used in various applications of pattern recognition, signal processin...