2. However, not all matrices work, such as the first one I tried yesterday. Here is an example of a matrix which does not work.
x
[,1] [,2] [,3] [,4] [1,] -0.4 -1.6 -1.0 -1.8 [2,] -2.2 -0.3 1.4 0.2
princomp(x)
Error in princomp(x) : covariance matrix is not non-negative definite
This does not happen with this example in Solaris, but I have had similar problems with eigen before and had to use something like eigen( (cv + t(cv))/2 ) to avoid it. It seems to me that if eigen is called with symmetric = TRUE, as is done in princomp, then eigen should return an error message about a non-symmetric matrix, rather than return a possibly spurious answer from which negative eigenvalues are checked to test for a non symmetric matrix. Paul Gilbert -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-devel-request@stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._