This paper presents the R package anacor for the computation of simple and canonical correspondence analysis with missing values. The canonical correspondence analysis is specified in a rather general way by imposing covariates on the rows and/or the columns of the two-dimensional frequency table. The package allows for scaling methods such as standard, Benzécri, centroid, and Goodman scaling. In addition, along with well-known two- and three-dimensional joint plots including confidence ellipsoids, it offers alternative plotting possibilities in terms of transformation plots, Benzécri plots, and regression plots
Homogeneity analysis combines the idea of maximizing the correlations between variables of a multiva...
AbstractWe compare correspondence analysis (CA) and the alternative approach using Hellinger distanc...
Correspondence Analysis (CA) is a multivariate method that has been developed from different perspec...
This paper presents the R package anacor for the computation of simple and canonical correspondence ...
This paper presents a description of the R package CAvariants. It performs six variants of correspon...
We describe an implementation of simple, multiple and joint correspondence analysis in R. The result...
This paper presents the R package CAvariants (Lombardo and Beh, 2017). The package performs six vari...
Correspondence Analysis (CA) is a statistical exploratory technique frequently used in many research...
AbstractCorrespondence Analysis (CA) is a statistical exploratory technique frequently used in many ...
Canonical correlations analysis (CCA) is an exploratory statistical method to highlight correlations...
The generalization of simple correspondence analysis, for two categorical variables, to multiple cor...
Correspondence Analysis (CA) is a statistical exploratory technique frequently used in many research...
Correspondence analysis (CA) is popular method for providing a graphical summary of the association ...
Correspondence analysis (CA) is popular method for providing a graphical summary of the association ...
Canonical correlations analysis (CCA) is an exploratory statistical method to highlight correlations...
Homogeneity analysis combines the idea of maximizing the correlations between variables of a multiva...
AbstractWe compare correspondence analysis (CA) and the alternative approach using Hellinger distanc...
Correspondence Analysis (CA) is a multivariate method that has been developed from different perspec...
This paper presents the R package anacor for the computation of simple and canonical correspondence ...
This paper presents a description of the R package CAvariants. It performs six variants of correspon...
We describe an implementation of simple, multiple and joint correspondence analysis in R. The result...
This paper presents the R package CAvariants (Lombardo and Beh, 2017). The package performs six vari...
Correspondence Analysis (CA) is a statistical exploratory technique frequently used in many research...
AbstractCorrespondence Analysis (CA) is a statistical exploratory technique frequently used in many ...
Canonical correlations analysis (CCA) is an exploratory statistical method to highlight correlations...
The generalization of simple correspondence analysis, for two categorical variables, to multiple cor...
Correspondence Analysis (CA) is a statistical exploratory technique frequently used in many research...
Correspondence analysis (CA) is popular method for providing a graphical summary of the association ...
Correspondence analysis (CA) is popular method for providing a graphical summary of the association ...
Canonical correlations analysis (CCA) is an exploratory statistical method to highlight correlations...
Homogeneity analysis combines the idea of maximizing the correlations between variables of a multiva...
AbstractWe compare correspondence analysis (CA) and the alternative approach using Hellinger distanc...
Correspondence Analysis (CA) is a multivariate method that has been developed from different perspec...