## S3 method for class 'mca':
print(x, ...)
## S3 method for class 'mca':
summary(object, ...)
## S3 method for class 'mca':
plot(x, ...)
## S3 method for class 'mca':
fitted(object, which=NA, components=FALSE, ...)
## S3 method for class 'mca':
residuals(object, which=NA, ...)
## S3 method for class 'mca':
predict(object, which=NA, newdata=NA, components=FALSE, ...)
mca-class
object.mca-class
object.mcaobj
is
untested.mca-class
objects contain:y
) and explanatory
(x
) variables that were given to MCA
.eigenmap-class
object that was given to
MCA
.U
) with variable
y
and x
, the codependence coefficients $\mathbf{c}$ and
the coregression coefficients $\mathbf{b}$.test.mca
or permute.mca
. NULL
if
no testing was performed, such as when only mca
had
been called. The results of statistical testing is a list containing
the following members:permute.mca
for permutation testing. 0
or FALSE
for parametric testing obtained using test.mca
.y
and
x
, in decreasing order of magnitude.test.table
. NULL
for parametric testing.fitted
, residuals
, and predict
methods return
a single-column matrix of fitted, residuals, or predicted values,
respectively. The fitted
and predict
methods return a
list a list when the parameter component
is TRUE
. The
list contains the fitted
or predicted
values as a first
item and a matrix components
as a second. This matrix has one
column for each statistically significant codependence coefficient.