Performs a principal components analysis and returns the results as an object of class PcaClassic (aka constructor).
PcaClassic(x, ...)
# S3 method for default
PcaClassic(x, k = ncol(x), kmax = ncol(x),
scale=FALSE, signflip=TRUE, crit.pca.distances = 0.975, trace=FALSE, ...)
# S3 method for formula
PcaClassic(formula, data = NULL, subset, na.action, ...)
An S4 object of class PcaClassic-class
which is a subclass of the
virtual class Pca-class
.
a formula with no response variable, referring only to numeric variables.
an optional data frame (or similar: see
model.frame
) containing the variables in the
formula formula
.
an optional vector used to select rows (observations) of the
data matrix x
.
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.
a numeric matrix (or data frame) which provides the data for the principal components analysis.
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
\(\Sigma_{j=1}^k l_j/\Sigma_{j=1}^r l_j >= 0.8\).
It is preferable to investigate the scree plot in order to choose the number
of components and then run again. Default is k=ncol(x)
.
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.
a value indicating whether and how the variables should be scaled
to have unit variance (only possible if there are no constant
variables). If scale=FALSE
(default) or scale=NULL
no scaling is
performed (a vector of 1s is returned in the scale slot). If scale=TRUE
the data are scaled to have unit variance. Alternatively it can be a function
like sd
or Qn
or a vector of length equal the number of columns
of x
. The value is passed to the underlying function and the result
returned is stored in the scale slot. Default is scale=FALSE
.
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
signflip = TRUE
criterion to use for computing the cutoff values for the orthogonal and score distances. Default is 0.975.
whether to print intermediate results. Default is trace = FALSE
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. tools:::Rd_expr_doi("10.18637/jss.v032.i03").
Pca-class
, PcaClassic-class
,