similar to: Quick question about princomp/biplot

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 list, I want to perform a biplot, using customized titels for the x and y axis. Setting xlab="" and ylab="" resulted in an error, e.g.: > data(USArrests) > biplot(princomp(USArrests),xlab="",ylab="") Error in biplot.default(t(t(scores[, choices])/lam), t(t(x$loadings[, : length of dimnames[1] not equal to array extent > How do I

Which is the parameter that is used to decrease the size of ylabs plotted in biplot? I tried playing with cex and cex.lab I am not getting it right pc <- princomp(USArrests) biplot(pc, xlabs = rep("", nrow(USArrests)),ylabs=(colnames(USArrests))) Thanks../Murli [[alternative HTML version deleted]]

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

I am doing a principle component analysis on a dataset with a lot of different variables and have constructed a biplot of the data. Unfortunately, as can be seen on the attached image, the biplot is very messy, cluttered, and hard to read. I have performed a few modifications including outlier removal from a few of the variables, which has made the plot better, however it still is too cluttered

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

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

Full_Name: Hinrich Göhlmann Version: 1.4.1 OS: Windows 2000 Submission from: (NULL) (148.177.130.121) Hi all, I've searched the known bugs and hopefully I did not oversee this one... When I have done a normal zz<-princomp(na.omit(raw.data)) and I then draw a biplot with biplot(zz,cex=c(.1,.7),col=c(5,1),choice=c(1,2),xlim=c(-2,2),ylim=c(-5,2)) the x axis gets set properly, but the y

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) # =^=

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

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",

Hello, I have a graphical problem concerning a biplot that I was ask to insert in a scientific work to be published. I've performed a princomp analysis and produce the relative biplot but the labels of variables are out of margin (see attached file). When I try to wide the x axis by the function xlim=c(i:j), nothing happens if not a partial shift of the x range. Is there any specific

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

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

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 all I would like to replace labels for x in biplot() with symbols (points) that will visually illustrate different classes/groups. After an unsuccessful search through the documents and archives, I turn to the list for help - any suggestions that can point me in the right direction? Thanks Mat Vanderklift

Hi R-community, I am doing a PCA and I need plots for different combinations of axes (e.g., PC1 vs PC3, and PC2 vs PC3) with the arrows indicating the loadings of each variables. What I need is exactly what I get using biplot (pca.object) but for other axes. I have plotted PC2 and 3 using the scores of the cases, but I don't get the arrows proportional to the loadings of each variables on

[was sent a wrong R-help address; manually resent by MM] Hello I'am using the 'biplot' and 'biplot.pincomp' functions of the 'mva' package for my studies. The biplot represents both the observations and the variables of a matrix of multivariate data on the same plot. The observations are represented by their numbers (the line of the data matrix), but I would need to

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

Hi all, I am using the vegan package to run a prcincipal components analysis on forest structural variables (tree density, basal area, average height, regeneration density) in R. However, I could not find out how to extract factor loadings (correlations of each variable with each pca axis), as is straightforwar in princomp. Do anyone know how to do that? Moreover, do anyone knows