Subscribers, What is my mistake with the following example: library(lattice) testmatrix<-matrix(c(1,2,3,4,3,6,12,24),nrow=4,ncol=2) testylabels<-c('w1','x1','y1','z1') dotplot(testmatrix, scales=list(y=list(testylabels)), xlab=NULL) #testylabels not shown, instead 'D' 'C' 'B' 'A' Thanks in advance. --
You are very close. The argument scales(list(y=list())) supports multiple arguments for the y axis so you need to tell lattice how to use testylabels: dotplot(testmatrix, scales=list(y=list(labels=testylabels), xlab=NULL)) ------------------------------------- David L Carlson Department of Anthropology Texas A&M University College Station, TX 77840-4352 -----Original Message----- From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of rl at openmailbox.org Sent: Monday, December 15, 2014 10:03 AM To: r-help at r-project.org Subject: [R] dotplot axes labelling Subscribers, What is my mistake with the following example: library(lattice) testmatrix<-matrix(c(1,2,3,4,3,6,12,24),nrow=4,ncol=2) testylabels<-c('w1','x1','y1','z1') dotplot(testmatrix, scales=list(y=list(testylabels)), xlab=NULL) #testylabels not shown, instead 'D' 'C' 'B' 'A' Thanks in advance. -- ______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
Dear Subscribers, how is it possible that the loadings of the second or even third component of a PLS-Analysis show higher values than the first component? Somebody got an idea?? Thanks in advance, Wolfgang -- Dipl. Geogr. Wolfgang Obermeier Faculty of Geography Philipps-University of Marburg Deutschhausstr. 12 D-35032 Marburg +49 (0)6421 28 24204
Wolfgang Obermeier <wolfgang.obermeier at geo.uni-marburg.de> writes:> how is it possible that the loadings of the second or even third component of > a PLS-Analysis show higher values than the first component? Somebody got an > idea??The loadings of a PLS regression are simply the coefficients that are multiplied with the X variables to transform X to the "latent vectors" used in the regression (this is slightly over-simplified). There is no reason why the coefficients of the first component should be larger than the coefficients of other components. (In fact, it is often the case that when one fits too many components (i.e., one starts to model "noise"), the coefficients of the last components get higher and higher.) -- Regards, Bj?rn-Helge Mevik