print.CAvariants {CAvariants}

Main printing function for numerical summaries

Description

This function prints the numerical output for any of the six variants of correspondence analysis called by catype.
The input parameter is the name of the output of the main function CAvariants.

Usage

## S3 method for class 'CAvariants'
print(x, printdims = 2, ellcomp = TRUE, digits = 3,...) 

Arguments

x

The name of the output object from the main function CAvariants.

printdims

The number of dimensions that are used for summarising the numerical output of the analysis. By default, printdims = 2. the maximum number is equal to the rank of the table.

ellcomp

This parameter specifies whether the characteristics of the confidence ellipses (eccentricity, semi-axis, area, p-values) are to be computed. By default, ellcomp = TRUE.

digits

The number of decimal places used for displaying the numerical summaries of the analysis. By default, digits = 3.

...

Further arguments passed to, or from, other functions.

Details

This function uses another function (called printwithaxes) for specifying the number of columns of a matrix to print.

Value

The output returned depends on the type of correspondence analysis that is performed

Xtable

The two-way contingency table.

Row weights: Imass

The row weight matrix. These weights depend on the type of analysis that is performed.

Column weights: Jmass

The column weight matrix. These weights are equal to the column marginal relative frequencies for all types of analysis performed.

Total inertia

The total inertia of the analysis performed. For example, for variants of non symmetrical correspondence analysis, the output produced includes the numerator of the Goodman-Kruskal tau index, its C-statistic and p-value.

Inertias

The inertia values, their percentage contribution to the total inertia and the cumulative percent inertias for the row and column variables.

Generalised correlation matrix

The matrix of generalised correlations when performing an ordered correspondence analysis, catype must be "DOCA", "DONSCA", "SOCA" or "SONSCA".

Row principal coordinates

The row principal coordinates when catype = "CA" or catype = "NSCA".

Column principal coordinates

The column principal coordinates when catype = "CA" or catype = "NSCA".

Row standard coordinates

The row standard coordinates when catype = "CA" or catype = "NSCA".

Column standard coordinates

The column standard coordinates when catype = "CA" or catype = "NSCA".

Row principal polynomial coordinates

The row principal polynomial coordinates when performing an ordered correspondence analysis.

Column principal polynomial coordinates

The column principal coordinates when performing a doubly ordered correspondence analysis.

Row standard polynomial coordinates

The row standard polynomial coordinates, when performing an ordered variant of correspondence analysis.

Column standard polynomial coordinates

The column standard polynomial coordinates, when performing an ordered variant of correspondence analysis.

Row distances from the origin of the plot

The squared Euclidean distance of the row categories from the origin of the plot.

Column distances from the origin of the plot

The squared Euclidean distance of the column categories from the origin of the plot.

Polynomial components

The polynomial components of the total inertia and their p-values. The total inertia of the column space is partitioned to identify polynomial components. when catype = "SOCA" or catype = "SONSCA". When catype = "DOCA" or catype = "DONSCA", the total inertia of both the row and column space is partitioned to give the polynomial components.

Inner product

The inner product of the biplot coordinates for the two-dimensional plot.

eccentricity

Value of ellipse eccentricity, the distance between its center and either of its two foci, It can be thought of as a measure of how much the conic section deviates from being circular.

HL Axis 1

Value of ellipse semi-axis 1 for each row and column points.

HL Axis 2

Value of ellipse semi-axis 2 for each row and column points.

Area

Ellipse area for each row and column points.

pvalcol

P-value for each row and column points.

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.

Examples

data(asbestos)
resasbestos <- CAvariants(asbestos, catype = "DOCA") 
print(resasbestos)