compsonetable.exe {CAvariants}R Documentation

Polynomial component of inertia in column space

Description

This function allows the analyst to compute the contribution that the polynomial components make to the inertia (Pearson's chi-squared statistic or the Goodman-Kruskal tau index). The ordered variable should be the column variable that is transformed by polynomials. The polynomial components are the column polynomial components. The given input matrix is the Z matrix of generalised correlations from the hybrid decomposition. It is called by CAvariants when catype = "SOCA" or catype = "SONSCA".

Usage

compsonetable.exe(Z)

Arguments

Z

The matrix of generalised correlations between the polynomial and principal axes.

Value

The value returned is the matrix

comps

The matrix of the column polynomial component of inertia.

Note

This function belongs to the class called cacorporateplus.

Author(s)

Rosaria Lombardo and Eric J. Beh

References

Beh EJ and Lombardo R 2014 Correspondence Analysis: Theory, Practice and New Strategies. Wiley.
Lombardo R Beh EJ 2016 Variants of Simple Correspondence Analysis. The R Journal, 8 (2), 167–184.
Lombardo R Beh EJ and Kroonenberg PM 2016 Modelling Trends in Ordered Correspondence Analysis Using Orthogonal Polynomials. Psychometrika, 81(2), 325–349.


[Package CAvariants version 5.6 Index]