Summary: The aim of this paper is to propose a new operational measure for evaluating the degree of dependence existing between two nominal categorical variables. Given an r×c table T, representing bivariate statistical data, our approach to measure the strength of this relation is based on the consideration of the class of all contingency tables with the same margins as T. Once a partial or total ordering of dependence in (as defined in Greselin and Zenga [2004b]) has been given, the relative position assumed by T in can be a meaningful measure of dependence. Some desirable properties of these indices are presented: by construction, they are normalized, coherent with each level of ordering and attain extreme values in extreme dependence...
Recently, the analysis of ordered and non-ordered categorical variables has assumed a relevant role,...
Two families of dependence measures between random variables are introduced. They are based on the R...
The problem of dependency between two random variables has been studied throughly in the literature....
In this paper a new index to analyse the dependence between categorical variables is presented and i...
In this paper a new index to analyse the dependence between categorical variables is presented and i...
Interest in assessing the degree of association between random variables, meaning the strengh of th...
Interest in assessing the degree of association between random variables, meaning the strengh of th...
none3siTitolo della collana: Series: Springer Optimization and Its ApplicationsInterest in assessing...
The most common measure of dependence is the correlation coefficient. Its problem is that it can be ...
AbstractIn this paper, we introduce a new copula-based dependence order to compare the relative degr...
The paper is devoted to the multivariate measures of dependence. In contrast to the classical approa...
In applied research many data sets contain observations from ordinal variables rather than continuou...
This article focuses on a statistical tool for dependence analysis in scientific research. Starting ...
The final publication is available at link.springer.comWe propose new dependence measures for two re...
We extend rank-based dependence measures like Spearman's rho to categorical data so that the same 1 ...
Recently, the analysis of ordered and non-ordered categorical variables has assumed a relevant role,...
Two families of dependence measures between random variables are introduced. They are based on the R...
The problem of dependency between two random variables has been studied throughly in the literature....
In this paper a new index to analyse the dependence between categorical variables is presented and i...
In this paper a new index to analyse the dependence between categorical variables is presented and i...
Interest in assessing the degree of association between random variables, meaning the strengh of th...
Interest in assessing the degree of association between random variables, meaning the strengh of th...
none3siTitolo della collana: Series: Springer Optimization and Its ApplicationsInterest in assessing...
The most common measure of dependence is the correlation coefficient. Its problem is that it can be ...
AbstractIn this paper, we introduce a new copula-based dependence order to compare the relative degr...
The paper is devoted to the multivariate measures of dependence. In contrast to the classical approa...
In applied research many data sets contain observations from ordinal variables rather than continuou...
This article focuses on a statistical tool for dependence analysis in scientific research. Starting ...
The final publication is available at link.springer.comWe propose new dependence measures for two re...
We extend rank-based dependence measures like Spearman's rho to categorical data so that the same 1 ...
Recently, the analysis of ordered and non-ordered categorical variables has assumed a relevant role,...
Two families of dependence measures between random variables are introduced. They are based on the R...
The problem of dependency between two random variables has been studied throughly in the literature....