Add to ORKGWe describe an implementation of simple, multiple and joint correspondence analysis in R. The resulting package comprises two parts, one for simple correspondence analysis and one for multiple and joint correspondence analysis. Within each part, functions for computation, summaries and visualization in two and three dimensions are provided, including options to display supplementary points and perform subset analyses. Special emphasis has been put on the visualization functions that offer features such as different scaling options for biplots and three-dimensional maps using the rgl package. Graphical options include shading and sizing plot symbols for the points according to their contributions to the map and masses respectively
In correspondence analysis rows and columns of a nonnegative data matrix are depicted as points in a...
Over the years Correspondence Analysis has become a valuable tool for archaeologists because it enab...
In a recent issue of this journal, M.J. Baxter and H.E.M. Cool published an interesting article on t...
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...
The generalization of simple correspondence analysis, for two categorical variables, to multiple cor...
This paper presents a description of the R package CAvariants. It performs six variants of correspon...
This paper presents the R package anacor for the computation of simple and canonical correspondence ...
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 ...
The generalization of simple (two-variable) correspondence analysis to more than two categorical var...
The purpose of this monograph is to provide a nontechnical introduction to Multiple Correspondence A...
The generalization of simple (two-variable) correspondence analysis to more than two categorical var...
”compositions” is a new R-package for the analysis of compositional and positive data.It contains fo...
In correspondence analysis rows and columns of a nonnegative data matrix are depicted as points in a...
Over the years Correspondence Analysis has become a valuable tool for archaeologists because it enab...
In a recent issue of this journal, M.J. Baxter and H.E.M. Cool published an interesting article on t...
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...
The generalization of simple correspondence analysis, for two categorical variables, to multiple cor...
This paper presents a description of the R package CAvariants. It performs six variants of correspon...
This paper presents the R package anacor for the computation of simple and canonical correspondence ...
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 ...
The generalization of simple (two-variable) correspondence analysis to more than two categorical var...
The purpose of this monograph is to provide a nontechnical introduction to Multiple Correspondence A...
The generalization of simple (two-variable) correspondence analysis to more than two categorical var...
”compositions” is a new R-package for the analysis of compositional and positive data.It contains fo...
In correspondence analysis rows and columns of a nonnegative data matrix are depicted as points in a...
Over the years Correspondence Analysis has become a valuable tool for archaeologists because it enab...
In a recent issue of this journal, M.J. Baxter and H.E.M. Cool published an interesting article on t...