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.
# S3 method for CAvariants
print(x, printdims = 2, ellcomp = TRUE, digits = 3,...)
The output returned depends on the type of correspondence analysis that is performed
The two-way contingency table.
The row weight matrix. These weights depend on the type of analysis that is performed.
The column weight matrix. These weights are equal to the column marginal relative frequencies for all types of analysis performed.
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.
The inertia values, their percentage contribution to the total inertia and the cumulative percent inertias for the row and column variables.
The matrix of generalised correlations when performing
an ordered correspondence analysis, catype must be "DOCA", "DONSCA", "SOCA" or "SONSCA".
The row principal coordinates when catype = "CA" or catype = "NSCA".
The column principal coordinates when catype = "CA" or catype = "NSCA".
The row standard coordinates when catype = "CA" or catype = "NSCA".
The column standard coordinates when catype = "CA" or catype = "NSCA".
The row principal polynomial coordinates when performing an ordered correspondence analysis.
The column principal coordinates when performing a doubly ordered correspondence analysis.
The row standard polynomial coordinates, when performing an ordered variant of correspondence analysis.
The column standard polynomial coordinates, when performing an ordered variant of correspondence analysis.
The squared Euclidean distance of the row categories from the origin of the plot.
The squared Euclidean distance of the column categories from the origin of the plot.
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.
The inner product of the biplot coordinates for the two-dimensional plot.
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.
Value of ellipse semi-axis 1 for each row and column points.
Value of ellipse semi-axis 2 for each row and column points.
Ellipse area for each row and column points.
P-value for each row and column points.
The name of the output object from the main function CAvariants.
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.
This parameter specifies whether the characteristics of the confidence ellipses (eccentricity, semi-axis, area, p-values)
are to be computed. By default, ellcomp = TRUE.
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.
Rosaria Lombardo and Eric J. Beh
This function uses another function (called printwithaxes) for specifying the number of
columns of a matrix to print.
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.
data(asbestos)
resasbestos <- CAvariants(asbestos, catype = "DOCA")
print(resasbestos)
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