similar to: How do I view hidden methods?

[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

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() ##

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

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:

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

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

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) # =^=

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

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

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]]

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

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

Just installed R-1.7.0 (with recommended libraries) on RedHat 8.0. At R console, I can do > library (MASS) > just fine. However, if I put a line 'library(MASS)' into ~/.Rprofile, it fails to load, R : Copyright 2003, The R Development Core Team Version 1.7.0 (2003-04-16) .... Type `q()' to quit R. Error in get(x, envir, mode, inherits) : variable "biplot" was

Hi, I am doing PCA on several columns of data in a data.frame. I am interested in particular rows of data which may have a particular combination of 'types' of column values (without any pre-conception of what they may be). I do the following... # My data table. allDat <- read.table("big_select_thresh_5", header=1) # Where some rows look like this... # PDB SUNID1

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 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

Greetings, I am working on a stylometric analysis of some latin texts; one of the latest stylometric techniques involves using principal components analysis. Not being a statistician, I can't really fully rely on PCA as my primary tool, since I don't really understand the statistics behind the PCA technique. Nevertheless, the ability to use PCA and graph the results has been

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

Hello, Is there any possibility in R to see the body of the non-visible function, for example princomp? If I do : > methods(princomp) so, I get that princomp.default and princomp.formula are non-visible functions and body(princomp.default) doesnt show it. In particular, I guess I have a very nave question Id like to see how scores calculation is implemented in the function princomp.