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.