You are wrong. No covariance matrix is computed. Please don't "speculate" -- read the Help file which clearly states:
"The calculation is done by a singular value decomposition of the (centered and possibly scaled) data matrix, not by using eigen on the covariance matrix. This is generally the preferred method for numerical accuracy. " -- Bert Gunter > I speculate that the underlying function transposes the > input data matrix and computes the the TxT [rather than SxS] > covariance matrix and solves for the eigenvalues/vectors. > It then uses a linear transformation to get the results > for the original input data matrix. > > Computationally, the above is much faster and uses less memory. > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
