As Bert suggests, the help file explains the differences between princomp and prcomp. Look under the Details section ?princomp ?prcomp
# the first PC using princomp a <- princomp(USArrests, cor=TRUE) a1 <- a$scores[, 1] # the first PC using prcomp # use center=TRUE and scale.=TRUE for the equivalent of cor=TRUE in princomp() b <- prcomp(USArrests, center=TRUE, scale.=TRUE) b1 <- b$x[, 1] # the results are nearly the same plot(a1, b1) abline(0, 1, col="red") abline(lsfit(a1, b1)) Jean Bert Gunter <gunter.ber...@gene.com> wrote on 08/22/2012 11:42:57 PM: > > How about reading the Help files? > > -- Bert > > On Wed, Aug 22, 2012 at 8:34 PM, jpm miao <miao...@gmail.com> wrote: > > Hi , > > > > To my knowledge, there're two functions that can do principal component > > analysis, princomp and prcomp. > > > > I don't really know the difference; the only thing I know is that when > > the sample size < number of variable, only prcomp will work. Could someone > > tell me the difference or where I can find easy-to-read reference? > > > > To access the first PC using princomp: > > Mpca<-princomp(M, cor=T) > > Mpca$scores[,1] > > > > How can I access the first PC using prcomp? > > Mpca<-prcomp(M) > > > > Is there an option for "cor=T"? > > In case where both functions work, will the results be the same? > > > > Thanks, > > > > Miao > > > > -- > > Bert Gunter > Genentech Nonclinical Biostatistics > > Internal Contact Info: > Phone: 467-7374 > Website: > http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/ > pdb-biostatistics/pdb-ncb-home.htm [[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.
