search for: baumgaertel

Hi, how can I scale the x- and y-axis of a "plot" to the same scale? My problem: The following command sequence produces the plot in a square. What I want is the x-axis to be 5 times as wide (measured e.g. in pixels) as the y-axis is long (because y ranges from -1 to 1 and x ranges from 0 to 10). x <- seq( from=0, to=10, by=.1) sinx <- sin(x) plot( x, sinx, type="l")

hello list, when I use method lda of the MASS package I experience a warning: variables are collinear in: lda.default(data[train, ], classes[train]) Is there an easy way to recover from this issue within the MASS package? Or how can I tell how severe this issue is at all? I understand that I shouldn't use lda at all with collinear data and should use "quadratische" (squared?)

hi all, I've got to import CSV-datasets (with variable-names in the first line) into data.frames. each is about 12MB (or more!) with 1823 columns and about 500 rows. the first 22 columns are in "character"-mode, the rest is "numeric". I run R 1.4.1 on a Windows 2000 system. First I tried read.table() which works fine for a low number of cases (say, 40). with all cases

Hi all, currently I'm working with physical data stored in a data.frame. I have N observations, typically 100-300 per data set. Each row in a set holds M (typically 2100) variables which represent a curve. For linear discriminant analysis I chose first to do a wavelet transform (because M >> N) and then feed the transformed data (of level L) in lda. This works fine (e.g. error <

org.omegahat.R.Java.REvaluator e = new org.omegahat.R.Java.REvaluator(); Object val = e.eval("objects()"); if(val != null) { String[] objects = (String[])val; for(int i = 0 ; i < objects.length; i++) System.err.println("("+i+") " + objects[i]); } hello, thanks to Philippe Grosjean's work I finally got SJava working (on Windows XP!!), so that I can

hello all, for my diploma-thesis i want to statitically analyze near-infrared-spectra. a spectrum is given by the y-values of 1038 equi-distant x-points. in nature, a spectrum is a continuous curve. for analysis, every x-point is seen as a statistical variable. now my problem: first, i read a csv-table in a data.frame called sTable via read.table. besides some meta-data there are 1038 variables

hi, does anyone already have implemented in R the Best-Basis Algorithm or the Local Discriminant Basis Algorithm using wavelets? for those interested: both algorithms are described in N. Saito, R. R. Coifman: "Local Discriminant Bases" (SPIE vol. 2303, 1994) and can be downloaded here: ftp://pascal.math.yale.edu/pub/wavelets/papers/ldb.ps.gz thanks, till -- ALL THESE WORLDS

Hello, using the lda-method from MASS-package I was wondering whether there is a built-in method for figuring out Wilks' Lambda? Searching the Web I found in the r-help archive a thread form june 2002, but it didn't help me. I understand I can use manova and its summary-method to get Wilks' Lambda on the screen, but I don't see the connection to lda from MASS. Or does