Description Contents Future prospects Author Acknowledgements

This package provides functions and methods for performing correspondence regression, i.e. the correspondence analysis of the
crosstabulation of a categorical variable Y in function of another one X, where X can in turn be made up of the combination of various
categorical variables.
Consequently, correspondence regression can be used to analyze the effects for a polytomous or multinomial outcome variable.
The central function in the package is `corregp`

, which enables methods for printing, summarizing and plotting the output.
Additionally, there are functions for computing confidence intervals, ellipses or 3D ellipsoids (by means of bootstrapping).

This package consists of the following datasets, functions, generics and methods:

`HairEye`

Hair and eye color of statistics students (data frame).`COMURE`

The use of linguistic variants in translations vs. non-translations and in six different registers.`TSS`

The use of inflected or uninflected determiners in vernacular Belgian Dutch.

`ci`

A helper function to compute confidence intervals on the basis of a numeric vector.`confGet`

An internal function to retrieve the`conf`

components in a`corregp`

object.`corregp`

The basic function to perform correspondence regression. Typically, one starts here, and then one uses`print`

,`summary`

,`anova`

,`screeplot`

or`plot`

methods.

`cint`

Compute confidence intervals.`cell`

Compute confidence ellipses.`cell3d`

Compute 3D confidence ellipsoids.`ciplot`

Plot confidence intervals.`pcplot`

Plot parallel coordinates.`agplot`

Plot an association graph.`plotag`

Plot an association graph.

`print.corregp`

Print the output of a correspondence regression.`summary.corregp`

Give a`summary`

of a correspondence regression.`print.summary.corregp`

Print the`summary`

of a correspondence regression.`screeplot.corregp`

Make a scree plot on the basis of the output of a correspondence regression.`anova.corregp`

Give an`anova`

table on the basis of a correspondence regression.`print.anova.corregp`

Print an`anova`

table on the basis of a correspondence regression.`coef.corregp`

Give the coefficients on the basis of a correspondence regression.`coefficients.corregp`

Give the coefficients on the basis of a correspondence regression.`fitted.corregp`

Give the fitted values on the basis of a correspondence regression.`fitted.values.corregp`

Give the fitted values on the basis of a correspondence regression.`residuals.corregp`

Give the residuals on the basis of a correspondence regression.`resid.corregp`

Give the residuals on the basis of a correspondence regression.`cint.corregp`

Compute confidence intervals on the basis of the output of a correspondence regression. Typically, this function is not so much used directly as it is called by a`ciplot.corregp`

command.`ciplot.corregp`

Plot confidence intervals on the basis of the output of a correspondence regression.`pcplot.corregp`

Make a parallel coordinate plot on the basis of the output of a correspondence regression.`cell.corregp`

Compute confidence ellipses on the basis of the output of a correspondence regression. Typically, this function is not so much used directly as it is called by a`plot.corregp`

command.`plot.corregp`

Plot the output (and the optional confidence ellipses) of a correspondence regression.`cell3d.corregp`

Compute 3D confidence ellipsoids on the basis of a correspondence regression. Typically, this function is not so much used directly as it is called by a`plot3d.corregp`

command.`plot3d.corregp`

Plot the 3D output (and the optional confidence ellipsoids) of a correspondence regression.`agplot.corregp`

Make an association graph on the basis of the output of a correspondence regression.`plotag.corregp`

Make an association graph on the basis of the output of a correspondence regression.

Specify a

`predict`

method for a.o. supplementary points.Enable scale transformations for all plots (and corresponding confidence regions).

Provide the possibility for so-called "calibration lines".

Koen Plevoets, [email protected]

This package has benefited greatly from the helpful comments of Isabelle Delaere and Gert De Sutter. Thanks to Kurt Hornik and Uwe Ligges for proofing this package.

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