AbstractThe local dependence function is constant for the bivariate normal distribution. Here we identify all other distributions which also have constant local dependence. The key property is exponential family conditional distributions and a linear conditional mean. When given two marginal distributions only, this characterisation is not very helpful, and numerical solutions are necessary
AbstractIn this paper, the dependence of uncorrelated statistics is studied. Examples of uncorrelate...
summary:In this paper, we study a general structure for the so-called Farlie-Gumbel-Morgenstern (FGM...
Cox and Wermuth proposed that the partial derivative of the conditional distribution function of a r...
AbstractThe local dependence function is constant for the bivariate normal distribution. Here we ide...
In several previous publications we developed an idea how probability tools can be used to measure s...
The local dependence function (LDF) describes changes in the correlation structure of continuous biv...
The local dependence function (LDF) describes changes in the correlation structure of continuous biv...
This paper discusses two graphical methods for the investigation of local association of two continu...
Models characterizing the asymptotic dependence structures of bivariate distributions have been intr...
There is often more structure in the way two random variables are associated than a single scalar de...
In the context of recent interest in extending scalar association measures to local association func...
We follow the ideas of measuring strength of dependence between random events, presented at two prev...
In this paper, some concepts of negative dependence for bivariate distributions, especially hazard ...
Let X,Y be two continuous random variables. Investigating the regression dependence of Y on X, resp...
AbstractThis paper concerns the rate of convergence in the central limit theorem for certain local d...
AbstractIn this paper, the dependence of uncorrelated statistics is studied. Examples of uncorrelate...
summary:In this paper, we study a general structure for the so-called Farlie-Gumbel-Morgenstern (FGM...
Cox and Wermuth proposed that the partial derivative of the conditional distribution function of a r...
AbstractThe local dependence function is constant for the bivariate normal distribution. Here we ide...
In several previous publications we developed an idea how probability tools can be used to measure s...
The local dependence function (LDF) describes changes in the correlation structure of continuous biv...
The local dependence function (LDF) describes changes in the correlation structure of continuous biv...
This paper discusses two graphical methods for the investigation of local association of two continu...
Models characterizing the asymptotic dependence structures of bivariate distributions have been intr...
There is often more structure in the way two random variables are associated than a single scalar de...
In the context of recent interest in extending scalar association measures to local association func...
We follow the ideas of measuring strength of dependence between random events, presented at two prev...
In this paper, some concepts of negative dependence for bivariate distributions, especially hazard ...
Let X,Y be two continuous random variables. Investigating the regression dependence of Y on X, resp...
AbstractThis paper concerns the rate of convergence in the central limit theorem for certain local d...
AbstractIn this paper, the dependence of uncorrelated statistics is studied. Examples of uncorrelate...
summary:In this paper, we study a general structure for the so-called Farlie-Gumbel-Morgenstern (FGM...
Cox and Wermuth proposed that the partial derivative of the conditional distribution function of a r...
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