Description Usage Arguments Value Note Author(s) References See Also
Performs a principal components analysis and returns the results as an object of class PcaClassic (aka constructor).
1 2 3 4 5 |
formula |
a formula with no response variable, referring only to numeric variables. |
data |
an optional data frame (or similar: see
|
subset |
an optional vector used to select rows (observations) of the
data matrix |
na.action |
a function which indicates what should happen
when the data contain |
... |
arguments passed to or from other methods. |
x |
a numeric matrix (or data frame) which provides the data for the principal components analysis. |
k |
number of principal components to compute. If |
kmax |
maximal number of principal components to compute.
Default is |
scale |
a logical value indicating whether the variables should be
scaled to have unit variance. Alternatively, a vector of length equal
the number of columns of x can be supplied. The value is passed to
scale and the result of the scaling is stored in the |
signflip |
a logical value indicating wheather to try to solve the sign indeterminancy of the loadings -
ad hoc approach setting the maximum element in a singular vector to be positive. Default is |
trace |
whether to print intermediate results. Default is |
An S4 object of class PcaClassic-class
which is a subclass of the
virtual class Pca-class
.
This function can be seen as a wrapper arround prcomp() from stats
which
returns the results of the PCA in a class compatible with the object model for robust PCA.
Valentin Todorov valentin.todorov@chello.at
Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. Journal of Statistical Software, 32(3), 1–47. URL http://www.jstatsoft.org/v32/i03/.
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