This function prints the results of any of the specified six variants of correspondence analysis.
The input parameter is the name of the output of the main function CAvariants.
# S3 method for CAvariants
print(x, printdims = 2, ellprint = TRUE, Mell = min(nrow(x$Xtable), ncol(x$Xtable)) - 1,
alpha = 0.05, digits = 3,...)
The name of the output object, for example say res, used with the main function CAvariants.
The number of dimensions, printdims, that are used to generate the correspondence plot, or biplot,
and for summarising the numerical output of the analysis. By default, printdims = 2.
The flag parameter, ellprint, allows that the characteristics of the confidence ellipses (eccentricity, semi-axis, area, p-values) are displayed.
By default, ellprint = TRUE.
The number of axes Mell used for the construction of the confidence ellipses. By default,
it is equal to its maximum value, Mell = min(nrow(x$Xtable), ncol(x$Xtable)) - 1, i.e. the rank of the data matrix.
This input parameter is identical to the parameter Mell of both the functions CAvariants and plot.CAvariants.
The level of significance used for the construction of the elliptical regions. By default, alpha = 0.05.
The minimum number of decimal places, digits, used for displaying the numerical summaries of the analysis.
By default, digits = 3.
Further arguments passed to or from other methods.
The value of output returned depends on the kind of correspondence analysis performed
The two-way contingency table.
The row weight matrix. These weights depend on the type of analysis performed.
The column weight matrix. These weights are equal to the data column margins for all types of analysis performed.
The total inertia of the analysis performed. For example, when considering the variants of non symmetrical correspondence analysis, the numerator of the Goodman-Kruskal tau index, the associated C-statistic and its p-value is produced.
The inertia values, their percentage contribution to the total inertia and the cumulative
percent inertias of the row and column space.
When performing an ordered correspondence analysis, this output summary describes both the row and column spaces
for each principal or polynomial axis. When catype is CA or NSCA,
the associated inertia values in the row and column spaces are identical. For all kind of variants, the absolute
and relative contributions of rows and columns are given.
The generalized correlation matrix when performing an ordered correspondence analysis,
catype should be "DOCA", "DONSCA", "SOCA" or "SONSCA".
The row principal coordinates when catype is "CA" or "NSCA".
The column principal coordinates when catype is "CA" or "NSCA".
The row standard coordinates when catype is "CA" or "NSCA".
The column standard coordinates when catype is "CA" or "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, i.e. standard polynomial coordinates for the row categories, when performing a doubly ordered correspondence analysis.
The column standard polynomial coordinates, i.e. standard polynomial coordinates for the column categories, when performing an ordered correspondence analysis.
The Euclidean distance of the row categories from the origin of the plot.
The 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 is "SOCA" or "SONSCA". When catype
is "DOCA" or "DONSCA", the total inertia of both the row and column space is partitioned to identify of polynomial components.
The inner product of the biplot coordinates (concerning the first two axes when firstaxis = 1 and lastaxis = 2).
When the input flag parameter is ellprint = TRUE, then the print includes the eccentricity of the confidence ellipses,
the semi-major axis length of the ellipse for each row and column point, HL Axis 1, the semi-minor axis length for the ellipse for each row and column point,
HL Axis 2, the area of the ellipse for each row and column point, Area and the p-value for each row and column point, P-value,
see also the parameter ellcomp of the function CAvariants for a detailed description of these parameters.
This function uses another function (called printwithaxes) for specifying the number of matrix dimensions to print.
Beh EJ and Lombardo R 2014 Correspondence Analysis: Theory, Practice and New Strategies. John Wiley & Sons. Lombardo R Beh EJ 2016 Variants of Simple Correspondence Analysis. The R Journal, 8 (2), 167--184.
# NOT RUN {
data(asbestos)
risasbestos<-CAvariants(asbestos, catype = "DOCA")
print(risasbestos)
# }
Run the code above in your browser using DataLab