PcaClassic | 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 = ncol(x), kmax = ncol(x),
scale=FALSE, signflip=TRUE, crit.pca.distances = 0.975, 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
|
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 value indicating whether and how the variables should be scaled
to have unit variance (only possible if there are no constant
variables). If |
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
|
crit.pca.distances |
criterion to use for computing the cutoff values for the orthogonal and score distances. Default is 0.975. |
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. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v032.i03")}.
Pca-class
, PcaClassic-class
,
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