lcovPca: Principal Component Analysis on a covariance object
Description
Performs PCA _and_ whitening on the covariance object
referenced by lcov. CAUTION: can be numerically instable
if covariance matrix is singular, better use LCOV_PCA2
instead /W. Konen/
Usage
lcovPca(lcov, dimRange = NULL)
Arguments
lcov
A list that contains all information about
the handled covariance-structure
dimRange
A number or vector for dimensionality
reduction:
if it is a number: only the first
components 1:dimRange are kept (those with largest
eigenvalues)
if it is a range: only the components in
the range dimRange[1]..dimRange[2] are kept
Value
returns a list: $W is the whitening matrix, $DW the
dewhitening matrix and $D an array containing a list of
the eigenvalues. $kvar contains the total variance kept
in percent.