This paper presents a description of the R package CAvariants. It performs six variants of correspondence analysis on a two-way contingency table. The main function that shares the same name as the package - CAvariants - allows the user to choose (via a series of input parameters) from six different correspondence analysis procedures. These include the classical approach to (symmetrical) correspondence analysis, singly ordered correspondence analysis, doubly ordered correspondence analysis, non symmetrical correspondence analysis, singly ordered non symmetrical correspondence analysis and doubly ordered non symmetrical correspondence analysis. The code provides the flexibility for constructing either a classical correspondence plot or a biplot graphical display. It also allows the user to consider other important features that allow for one to assess the reliability of the graphical representations, such as the inclusion of algebraically derived elliptical confidence regions. This paper provides R functions that elaborates more fully on the code presented in Beh and Lombardo (2014).

Variants of Simple Correspondence Analysis

LOMBARDO, Rosaria
;
2016

Abstract

This paper presents a description of the R package CAvariants. It performs six variants of correspondence analysis on a two-way contingency table. The main function that shares the same name as the package - CAvariants - allows the user to choose (via a series of input parameters) from six different correspondence analysis procedures. These include the classical approach to (symmetrical) correspondence analysis, singly ordered correspondence analysis, doubly ordered correspondence analysis, non symmetrical correspondence analysis, singly ordered non symmetrical correspondence analysis and doubly ordered non symmetrical correspondence analysis. The code provides the flexibility for constructing either a classical correspondence plot or a biplot graphical display. It also allows the user to consider other important features that allow for one to assess the reliability of the graphical representations, such as the inclusion of algebraically derived elliptical confidence regions. This paper provides R functions that elaborates more fully on the code presented in Beh and Lombardo (2014).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/363116
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