PcaClassic {rrcov} | R Documentation |
Performs a principal components analysis and returns the results as an object of class PcaClassic (aka constructor).
PcaClassic(x, ...) ## Default S3 method: PcaClassic(x, k = 0, kmax = ncol(x), trace=FALSE, ...) ## S3 method for class 'formula': PcaClassic(formula, data = NULL, subset, na.action, ...)
formula |
a formula with no response variable, referring only to numeric variables. |
data |
an optional data frame (or similar: see
model.frame ) containing the variables in the
formula formula . |
subset |
an optional vector used to select rows (observations) of the
data matrix x . |
na.action |
a function which indicates what should happen
when the data contain NA s. The default is set by
the na.action setting of options , and is
na.fail if that is unset. The default is na.omit . |
... |
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 k is missing,
or k = 0 , the algorithm itself will determine the number of
components by finding such k that l_k/l_1 >= 10.E-3 and
Σ_{j=1}^k l_j/Σ_{j=1}^r l_j >= 0.8.
It is preferable to investigate the scree plot in order to choose the number
of components and the run again. Default is k=0 . |
kmax |
maximal number of principal components to compute.
Default is kmax=10 . If k is provided, kmax
does not need to be specified, unless k is larger than 10. |
trace |
whether to print intermediate results. Default is trace = FALSE |
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