similar to: Newbie question regarding graphing of Princomp object

I'm attempting to modify how biplot draws its red vectors (among other things). This is how I've started: Biplot <- function(xx, comps = c(1, 2), cex = c(.6, .4)) { ## Purpose: Makes a biplot with princomp() object to not show arrows ## ---------------------------------------------------------------------- ## Arguments: xx is an object made using princomp() ##

Dear R-helpers, The vectors in my biplot are completely obscured by the ~1400 labels R is printing on my biplot. I don't really care about the labels. How can I make the biplot without the annoying labels? See attached, if that helps you see my problem. Many thanks, Mark Na

Hi is there a way to plot only the loadings in a biplot (with the nice arrows), and to skip the scores? thanks christoph

Hi everyone. I performing a simple PCA using the princomp function. Then, I use the biplot function to show it. However, the function use line number to represent samples. I would like to know if there's a way to use a dot (point) instead of the line number when using the biplot function. With regards, Phil -- View this message in context:

x=rmvnorm(2000, rep(0, 6), diag(c(5, rep(1,5)))) x=scale(x, center=T, scale=F) pc <- princomp(x) biplot(pc) There are a bunch of red arrows plotted, what do they mean? I knew that the first arrow labelled with "Var1" should be pointing the most varying direction of the data-set (if we think them as 2000 data points, each being a vector of size 6). I also read from

Dear R helpers, When producing a PCA biplot, vectors of environmental variables (as red arrows with labels) and scores of the observations (black labels (observation names)) are plotted by default. How can I change the graphical output? Let's say I would like that the scores are plottet only as symbols and not text. The only solution I found was this post in the help archive

As of R 1.7.0, princomp no longer accept matrices with more coloumns than rows. I'm curious: Why was this decision made? I work a lot with data where more coloumns than rows is more of a rule than an exception (for instance spectroscopic data). To me, princomp have two advantages above prcomp: 1) It has a predict method, and 2) it has a biplot method. A biplot method shouldn't be too

Hi, I run the example for princomp for R211 I got the following error for biplot > ## The variances of the variables in the > ## USArrests data vary by orders of magnitude, so scaling is appropriate > (pc.cr <http://pc.cr> <- princomp(USArrests)) # inappropriate Erreur dans cov.wt(z) : 'x' must contain finite values only > princomp(USArrests, cor = TRUE) # =^=

Peter, As I understand your Q. You probably have data that is similar to each other like stock Prices for all RHS variable. In that case the difference between corr and cov is not significant; however, if your RHS contains totally dissimilar variables it matters a great deal. If x1 income, x2 job type, x3 Education level, etc..., then taking cov of these variables would not be desireable

Daniel M Gessel dixit: >Wouldn't Clang be a good option to generating unoptimized LLVM IR? More like broken ;-) sometimes at least. >On Nov 28, 2008, at 6:13 AM, Duncan Sands wrote: >> They are not really done by LLVM, because no optimizations are done >> on the >> LLVM IR. They are done by llvm-gcc, a front-end to LLVM: llvm-pcc, anyone? :þ //mirabilos --

Tanya M. Lattner dixit: >LLVMers, > >The 2.4 pre-release (v2) is available for testing: >http://llvm.org/prereleases/2.4/ Is it correct that there is no matching clang distfile? A checkout of clang r58548 does not build with the prerelease, seems to require a newer version of llvm-current. (But then, maybe it’d be best anyway if I port llvm-current to MirBSD, because it’ll be easier

> biplot standardGeneric for "biplot" defined from package "stats" function (x, ...) standardGeneric("biplot") <environment: 0x0d4444d8> Methods may be defined for arguments: x Use showMethods("biplot") for currently available ones. > > > showMethods("biplot") Function: biplot (package stats) x="ANY"

Dears, I've been learning biplot (Gabriel, 1971) and I found the function 'biplot', inside of the package 'stats', useful but, a bit limited. So, I'm thinking to start a colaborative package to enhance this methods to other multivariate methods. In this way, I would like to start it, making public a new function (biplot.pca, still in development, but running) that make

Hello, Something incredible (at least for me) has happen. Yesterday night I downloaded biplot.R to edit this function and add new features I wished. Namely I wanted to plot points belonging to different groups using different colors and symbols. I identified which part of the original code I had to modify. Then, I rename biplot by biplotes and executing biplotes(x), being x a princomp class

Dear R-help fellows good afternoon. I am struggling in the attempt to impose some graphical conditions (changing point symbols, colors, etc) to biplot function (I am using it to visualize the results of princomp) but I can't apparently manage to change anything but the axis... and I have been browsing manuals and vignettes without finding any explicit suggestions on how to operate... Can

Hi everybody, Excuse me for this silly question, but after searching the help archives I'm still unable to find my way to read the source code of the "biplot" function in R. I have installed the mvbutils package, and tried: > fixr(biplot) which only gives me: function (x, ...) UseMethod("biplot") with no further details.... I'd like to read the code to see if

Ein eingebundener Text mit undefiniertem Zeichensatz wurde abgetrennt. Name: nicht verf?gbar URL: https://stat.ethz.ch/pipermail/r-help/attachments/20070513/6557c355/attachment.pl

Hello all, I just started in on R today. I am at the point where I am trying to distinguish different groups of data (hydrochemical data) in biplot. I search and found a post about converting the sample number in biplot to a symbol like x or + "> temp <- matrix(runif(50), nrow=10) > temp.pca <- princomp(temp) > biplot(temp.pca, xlabs=c("A", "A",

Hi, I think that the documentation for the biplot function `biplot.princomp' is inconsistent with what it actually does. Here is what the documentation states: pc.biplot If true, use what Gabriel (1971) refers to as a "principal component biplot", with lambda = 1 and observations scaled up by sqrt(n) and variables scaled down by sqrt(n). Then inner products between

Hello, llvm-config contains: | my $LLVM_SRC_ROOT = q{/usr/ports/lang/llvm/w-llvm-58935-0/llvm}; | my $LLVM_OBJ_ROOT = q{/usr/ports/lang/llvm/w-llvm-58935-0/llvm}; However, these paths are temporary and do not exist after compilation. llvm-gcc is fine to pick up the installed copy of llvm; how do I go if I want the installed copy to no longer contain build/fake-install paths? gccas