On one dataset I have 220 cases of physical data (the variables represent points on a curve). The Original data set holds about 1800 variables but I reduce this to a power of 2 (32, 64, ...) with an approximation method so that the representation of one curve (one observation) with say 32 points (variables) does not differ too much from the original representation with 1800 variables.
What I was also wondering about: Why does lda tell me about warnings and not *errors*? thanks, till >-- Original Nachricht -- >What is the dimension of your data. i.e. how many observations and how many >variables do you have? > >-----Original Message----- >From: Till Baumgaertel [mailto:[EMAIL PROTECTED] >Sent: Monday, February 24, 2003 9:41 AM >To: [EMAIL PROTECTED] >Subject: [R] Mass: lda and collinear variables > > >hello list, > >when I use method lda of the MASS package I experience a warning: variables >are collinear in: lda.default(data[train, ], classes[train]) > >Is there an easy way to recover from this issue within the MASS package? >Or how can I tell how severe this issue is at all? > >I understand that I shouldn't use lda at all with collinear data and should >use "quadratische" (squared?) discr. analysis (by Welch) instead. Or is this >wrong? Could I do this in R? > >Thanks four your help, >Till Baumg�rtel > > > > > >________________________________________ >Abos online bestellen. Oder Leser werben und Pr�mie aussuchen. >http://www.epost.de/aboservice > >______________________________________________ >[EMAIL PROTECTED] mailing list http://www.stat.math.ethz.ch/mailman/listinfo/r-help ________________________________________ Abos online bestellen. Oder Leser werben und Pr�mie aussuchen. http://www.epost.de/aboservice ______________________________________________ [EMAIL PROTECTED] mailing list http://www.stat.math.ethz.ch/mailman/listinfo/r-help
