search for: pcas

Dear all: Subjects were measured two times (t1 and t2) on different variables (v1 ... vn). Between t1 and t2 there was an experimental manipulation. I computed two PCAs for time-points t1 and t2. Is it possible to combine both PCAs in order to get only one set of eigenvectors? Due to the experimental manipulation measurement values on time points t1 and t2 changed for each subject. Many thanks Stefan --

Hi, this may sound like a very stupid question and perhaps it is, so I apologise in advance if anyone feels bored by it. I have done some principal component analysis with prcomp and what I would like to do is to visualise the effect of a principal component, i.e. show a graph of my data and then show how that graph would change if I go, let's say, one standard deviation, in either

Hi all, I have a file of average SWE observations for 40 years at over 4,000 points and am attempting to do a spatiotemporal analysis of the data using PCA, much like this paper did using snow depth: http://journals.ametsoc.org/doi/pdf/10.1175/1520-0442%281998%29011%3C0856%3ATCIRWS%3E2.0.CO%3B2 I have followed the code in the link below by my loadings are far too small (For example, the paper

Hi all, I am doing bootstrap on a distance matrix, in which samples have been drawn with replacement. After that I do PCA on a resulted matrix, and these 2 steps are repeated 1000 times. pca(x) is a vector where I wanted to store all 1000 PCAs; and x is from 1 to 1000 SampleD is a new matrix after resampling; I am getting the following error message, which I don't understand: .... +pca(x)<-princomp(SampleD[i,j]) + } Error in eigen(cv, symmetric = TRUE) : infinite or missing values in 'x' Should I maybe not use a vector,...

Hi everyone, I'd like to project two pcas onto one device window. I plot my first PCA: biplot(prcomp(t(cerebdevmat)), var.axes=FALSE, cex=c(1,.1), pc.biplot=TRUE) Now I'd like to project the features of another PCA onto this graph. Any suggestions? I know this is easily done in MatLab but haven't figured it out in R. Th...

Hi there, I am plotting relative warp scores (equivalent to pca scores) and I want to label (color code and shape) the points by group. I can't figure out how to do this beyond simple plotting. plot(RW1, RW2); Do I need to make vectors of each group and then plot them separately onto the same plot? How do I go about this? Thanks! -- View this message in context:

...o PCA in R, so this might be a basical thing, but I cannot find anything on the net about it. I need to make a PCA plot with two response variables (df$resp1 and df$resp2) against eight metabolites (df$met1, df$met2, ...) and I don't have a clue how to do... and I've only used the simplest PCAs before, like this: pcaObj=prcomp(t(df[idx, c(40:47)])) biplot(pcaObj) Anyone who knows how to do? Best rageds, Joel _________________________________________________________________ Hitta hetaste singlarna på MSN Dejting! http://dejting.se.msn.com/channel/index.aspx?tr...

Hello Sir/Mam I am Nitish Kumar Mishra from IMTECH, Chandigarh, India. I want to calculate the Principal Component Analysis(PCA), PLS of the input file and find top 30 PCAs of this file using PLS in R. I am asking regarding Linux(Red Hat 9) operating system. I have downloaded PLS from Crains site and try to installed it, but don't installed it. How I can download and installed PLS(for PCA and PLS) in R using Linux. Please me how I can installed PLR in R(Linux). Th...

Hi! I am trying to know which habitat variables most affect bird counts in a radius of 100m. I obtained bird counts in 2751 spatial points, and measured percentage of 21 habitat variables in these points. I applied a mixed model using the "lmer" function to these data, but I do not know how to select the best model using AIC here. Is there a way to do this automatically with R?

Hi, Evgenia and I have copied an updated version of the mlbench package to CRAN which contains several new data sets. We have also changed some of the variable names to avoid name conflicts. Best, -- ------------------------------------------------------------------- Friedrich Leisch Institut f?r Statistik Tel: (+43 1) 58801 10715 Technische

Hi, Evgenia and I have copied an updated version of the mlbench package to CRAN which contains several new data sets. We have also changed some of the variable names to avoid name conflicts. Best, -- ------------------------------------------------------------------- Friedrich Leisch Institut f?r Statistik Tel: (+43 1) 58801 10715 Technische

How does one rotate the loadings from a principal component analysis? Help on function prcomp() from package mva mentions rotation: Arguments retx a logical value indicating whether the rotated variables should be returned. Values rotation the matrix of variable loadings (i.e., a matrix whose olumns contain the eigenvectors). The function princomp returns this in the element