I may not understand completely, but it seems you have a 45x45 distance matrix of stimuli and you want to use to determine which stimuli are similar. Wouldn't hierarchical clustering be a more straightforward approach?
?hclust ------------------------------------- David L Carlson Associate Professor of Anthropology Texas A&M University College Station, TX 77840-4352 -----Original Message----- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Bob Wiley Sent: Friday, April 26, 2013 4:33 PM To: r-help@r-project.org Subject: [R] prcomp( and cmdscale( not equivalent? Hello, I have a dilemma that I'm hoping the R gurus will be able to help resolve. For background: My data is in the form of a (dis)similarity matrix created from taking the inverse of normalized reaction times. That is, each cell of the matrix represents how long it took to distinguish two stimuli from one another-- a square matrix of 45X45 where the diagonal values are all zero (since this represents two identical stimuli). I have been using cmdscale with this matrix as the input-- So: X = cmdscale(mydata,k=44,add=FALSE,eig=TRUE)$points returns a 45x34 matrix because only 34 of the eigenvalues > 0 I then run prcomp on the (transposition of) this matrix: prcomp(t(X),scale.=TRUE) The goal is to take the original matrix of inverse reaction times and transform that data such that we have PCs that show how stimuli are grouping together-- high absolute value loadings/coordinates on a given dimension should reflect how similar the stimuli are to one another. My concern is that I'm not fully understanding the mathematics behind cmdscale( and prcomp(, and that I may just be losing a lot of information or introducting noise? Or is my approach theoretically sound... I've read a TON on this now but I can't see exactly what R is doing with these two functions. thank you! -bob JHU Robert (Bob) Wiley [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
