The core of the paper consists of the treatment of two special decompositions for correspondence analysis of two-way ordered contingency tables: the bivariate moment decomposition and the hybrid decomposition, both using orthogonal polynomials rather than the commonly used singular vectors. To this end, we will detail and explain the basic characteristics of a particular set of orthogonal polynomials, called Emerson polynomials. It is shown that such polynomials, when used as bases for the row and/or column spaces, can enhance the interpretations via linear, quadratic and higher-order moments of the ordered categories. To aid such interpretations, we propose a new type of graphical display-the <i>polynomial biplot</i>
International audienceWe propose a new approach to the combinatorial interpretations of linearizatio...
AbstractWe show combinatorially that the higher-order matching polynomials of several families of gr...
Review of Scientific Instruments, 78(11): pp. 796–825.We consider bivariate polynomials orthogonal o...
The core of the paper consists of the treatment of two special decompositions for correspondence an...
For more than 20 years variants of correspondence analysis have arisen that accommodate for the stru...
Correspondence analysis (CA) has gained a reputation for being a very useful statistical technique f...
We present an alternative approach to Multiple Correspondence Analysis (MCA) that is appropriate whe...
Correspondence analysis (CA) has gained a reputation for being a very useful statistical technique f...
In situations where the structure of one of the variables of a contingency table is ordered recent t...
Taguchi's statistic has long been known to be a more appropriate measure of association the dependen...
Abstract. An alternative approach to classical correspondence analysis was developed in [3] and invo...
Non-symmetrical correspondence analysis (NSCA) is a useful tool for graphically detecting the asymme...
Non-symmetrical correspondence analysis (NSCA) is a useful tool for graphically detecting the asymme...
In the framework of multi-way data analysis, this paper presents symmetrical and non-symmetrical va...
Correspondence analysis is a popular graphical tool used to analyse contingency tables. In the past,...
International audienceWe propose a new approach to the combinatorial interpretations of linearizatio...
AbstractWe show combinatorially that the higher-order matching polynomials of several families of gr...
Review of Scientific Instruments, 78(11): pp. 796–825.We consider bivariate polynomials orthogonal o...
The core of the paper consists of the treatment of two special decompositions for correspondence an...
For more than 20 years variants of correspondence analysis have arisen that accommodate for the stru...
Correspondence analysis (CA) has gained a reputation for being a very useful statistical technique f...
We present an alternative approach to Multiple Correspondence Analysis (MCA) that is appropriate whe...
Correspondence analysis (CA) has gained a reputation for being a very useful statistical technique f...
In situations where the structure of one of the variables of a contingency table is ordered recent t...
Taguchi's statistic has long been known to be a more appropriate measure of association the dependen...
Abstract. An alternative approach to classical correspondence analysis was developed in [3] and invo...
Non-symmetrical correspondence analysis (NSCA) is a useful tool for graphically detecting the asymme...
Non-symmetrical correspondence analysis (NSCA) is a useful tool for graphically detecting the asymme...
In the framework of multi-way data analysis, this paper presents symmetrical and non-symmetrical va...
Correspondence analysis is a popular graphical tool used to analyse contingency tables. In the past,...
International audienceWe propose a new approach to the combinatorial interpretations of linearizatio...
AbstractWe show combinatorially that the higher-order matching polynomials of several families of gr...
Review of Scientific Instruments, 78(11): pp. 796–825.We consider bivariate polynomials orthogonal o...