computes the covariance matrix from a princomp object. The number of components k can be given as input.
1  covPC(x, k, method)

x 
an object of class princomp. 
k 
number of PCs to use for covariance estimation (optional). 
method 
method how the PCs have been estimated (optional). 
There are several possibilities to estimate the principal components (PCs)
from an input data matrix, including the functions PCAproj
and
PCAgrid
. This function uses the estimated PCs to reconstruct
the covariance matrix. Not all PCs have to be used, the number k of
PCs (first k PCs) can be given as input to the function.
cov 
the estimated covariance matrix 
center 
the center of the data, as provided from the princomp object. 
method 
a string describing the method that was used to calculate the PCs. 
Heinrich Fritz, Peter Filzmoser <P.Filzmoser@tuwien.ac.at>
C. Croux, P. Filzmoser, M. Oliveira, (2007). Algorithms for ProjectionPursuit Robust Principal Component Analysis, Chemometrics and Intelligent Laboratory Systems, Vol. 87, pp. 218225.
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