similar to: problem using MASS corresp and mca functions

Dear list: I have tried MASS's mca function and SAS's PROC corresp on the farms data (included in MASS, also used as mca's example), the results are different: R: mca(farms)$rs: 1 2 1 0.059296637 0.0455871427 2 0.043077902 -0.0354728795 3 0.059834286 0.0730485572 4 0.059834286 0.0730485572 5 0.012900181 -0.0503121890 6

One can import data from Excel ODBC source, but of course it is user's responsibility to ensure that the data are consistent. Each worksheet in the Excel workbook can be accessed as a table (for example, for Sheet1, you should type "select * from [Sheet1$]". The worksheet should have first row containing the column names, and the data rows should follow (the

hi, My code: data<-matrix(data=c(0.425,0.5,0.75,0.125,0.25,0.475,0.375,0.25,0.625,0.5,0.1,0.125,0,0.25,0.25),nrow=3,ncol=5,byrow=TRUE, dimnames=list(c("Good","Medium","Bad"),c("Content","Logistic","Trainer","Supply","User contribution"))) plot(corresp(data,nf=2),xlim=c(-1,1),ylim=c(-1,1)); The plot is

Hi! If I do: plot(corresp(a, nf = 2),xlim=c(-1,2),ylim=c(-1,1)) while the xlim takes effect, the ylim does not, no matter the values given for ylim. Is this intentional? is this an error? (I think this might be related with line 41 in biplot.default in mva) (using R 1.6.2 on a linux (suse 7.3) box.) Thanks Agus Dr. Agustin Lobo Instituto de Ciencias de la Tierra (CSIC) Lluis Sole Sabaris

Hi, I have the following (probably trivial) problem: I am running a Windows 95 System and have setted the environment variables R_HOME and especillay R_USER in the autoexec.bat. The idea was, to invoke R at the startup to read in the files .Renviron and .Rprofile from my home directory, even when the current working directory is somewhere else. Subject to the manual it should work, but it does

I have re-built all the compiled packages for R 1.2.0 for Windows, and the set available in CRAN/bin/windows/contrib are now for rw1020. If you are upgrading to rw1020, please replace all the compiled packages you have downloaded by ones from this set. There a few packages available for the first time: RMySQL mlbench netCDF and a few that are not yet running on 1.2.0 on any platform hdf5

I have re-built all the compiled packages for R 1.2.0 for Windows, and the set available in CRAN/bin/windows/contrib are now for rw1020. If you are upgrading to rw1020, please replace all the compiled packages you have downloaded by ones from this set. There a few packages available for the first time: RMySQL mlbench netCDF and a few that are not yet running on 1.2.0 on any platform hdf5

Dear sirs, My name is Marcelo Grimaldi and i work for General Electric in the Six Sigma Program. Recently I became very interested in spectral analysis, because I think it can be applied to my job. I use Minitab 12 and i have heard that writing macros for spectral analysis in this software is very difficult. Could I perform this analysis in a easier way throught "R" ? Have you ever

Hi, I have a big data file (over 30,000 records) looks like this: 100, 20, 46, 70 103, 0, 22, 45 117, -1, 34, 65 120, 15, 0, 25 113, 0, -1, 32 142, -1, -1, 55 ..... I want to read only those records having positive values in all of the four columns. That is, I don't want to read record # 3, 5, and 6 into R. However, when I type: read.csv("data.csv", sep=",")

I'm experienced in statistics, but I am a first-time R user. I would like to use R for correspondence analysis. I have installed R (Mac OSX). I have used the package installer to install the CA package. I have run the following line with no errors to read in the data for a table: NonLuxury <- read.table("/Users/myUserName/Desktop/nonLuxury.data.txt") The R online help

Package: xen-utils-3.0.3-1 Version: 3.0.3-0-4 Severity: important # /etc/init.d/xend start Restarting XEN control daemon: xendTraceback (most recent call last): File "/usr/lib/xen-3.0.3-1/bin/xend", line 40, in <module> from xen.xend.server import SrvDaemon File "/usr/lib/xen-3.0.3-1/lib/python/xen/xend/server/SrvDaemon.py", line 17, in <module> import

Hello, I was wondering whether anyone out there knows of the solution to a problem that I'm having with the Fields package. I am getting the error message when I try and run the fields function tps (thin plate splines). Namely, for two different sets of variables, I get: > bout <- Tps( bvolcap, bdsm) Error in svd(tempM) : error 159 in dsvdc > wout <- Tps( wvolcap, wdsm)

Hi all, We're proud to announce... ========================================== PyPy 1.0: JIT compilers for free and more ========================================== Welcome to the PyPy 1.0 release - a milestone integrating the results of four years of research, engineering, management and sprinting efforts, concluding the 28 months phase of EU co-funding! Although still not mature enough

Hello, I am new to R and I have a question about the difference between correspondence analysis in R and SPSS. This is the input table I am working with (4 products and 18 attributes): > mytable 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 1 15 11 20 4 14 7 1 2 1 4 12 12 17 19 11 20 9 10 2 19 18 14 14 16 4 14 11 11 15 22 19 22 16 21 19 15 16 3 16 13 10 9 15 4 10 7 11 13 18

Dear R users, I m quite a novice in using R for factor analysis and I would need some help to choose the right function. I have a contingency table and I would like to perform a Correspondence analysis on this table, followed by a hirarchical clustering of my variables projected in on the first principal components. Here are my question : - what is the more appropriate function to do so ...

The current r-devel (aka R 1.7.0) now attaches the package "methods" by default at startup. A new option, "defaultPackages", is set to c("methods", "ctest") by default, causing the .First in package base to require those two packages at startup. There are two main known differences from having methods attached: - the definition of class() changes, in

I use R Version 0.60 Alpha (September 18, 1997) on a Linux Pentium (Debian 1.3) and on a Sparc-Sun-Solaris 2.5.=20 R> svd(matrix(1:16,4,4)) =09yields on both machines Error: error 4 in dsvdc R> svd(matrix(1:20,4,5)) =09gives a result on the Linux computer $d [1] 0 0 0 NA $u [,1] [,2] [,3] [,4] [1,] 1 0 0 0 [2,] 0 1 0 0 [3,] 0 0 1 0 [4,] 0

Dear all, I am interested in reading Excel spreadsheets (*.xls) directly into R (I am using version 1.1.1 at the moment). I have not had much luck so far. For the time being, I have been converting Excel files to comma delimited files (*.csv) and reading these into R (using commands such as "read.csv"). This works well, but it would be more efficient if I could read the Excel files

Is it possible to do a graphic in 3D? This is my source: but this one is on 2D and at moment variables put on other variables, so it is difiicult to differentiate them visibly. plot(corresp(data,nf=2),xlim=c(-1,1),ylim=c(-1,1)); Thanks Sabine --------------------------------- ils, photos et vidéos ! [[alternative HTML version deleted]]

Thanks for all the helpful responses. I include the data file and the syntax file for reference. Again, if I use the fields function, as is, I get the message: Error in svd(tempM) : error 159 in dsvdc using traceback, I get: > traceback() 4: stop(paste("error ", z$info, " in dsvdc")) 3: svd(tempM) 2: Krig(x, Y, cov.function = rad.cov, m = m, decomp = decomp,