similar to: "Best" Out of box Linux distro for R

Probably wrong group for this, but a quick question. I've just switched from emacs to Xemacs. In reinstalling ESS 5.1.19 I keep getting the following error when loading Xemacs: "Error in init file: Symbol's function definition is void: w32-using-nt" I've debugged the ess-site.el file, which is where the error originates from. The line causing the difficulty is:

David Brahm's initial post seems to me to be filled with a mixture of bugs, wants, and needs coupled with a desire to "make" R become S-Plus. David, if S-Plus works for you, why are you bothering to convert all your code to R? No one has ever asserted that R==S (or S-Plus), and there is no reason to expect this equality to hold, ever. R is open source. If you want to change

Are there any S-Plus or R libraries/packages that do Finite Mixture Analysis following the algorithms similar to those implemented in Geoffrey MacLachlan's EMMIX program? Thanks. Dr. Marc R. Feldesman email: feldesmanm at pdx.edu email: feldesman at attglobal.net fax: 503-725-3905 "Don't know where I'm going. Don't like where I've been. There may be no exit. But

I just updated rpart to the latest version (3.1.0). There are a number of changes between this and previous versions, and some of the code I've been using with earlier versions (e.g. 3.0.2) no longer work. Here is a simple illustration of a problem I'm having with xpred.rpart. iris.test.rpart<-rpart(iris$Species~., data=iris[,1:4], parms=list(prior=c(0.5,0.25, 0.25))) + ) >

Our lab just picked up a G4 Powerbook (1 GHz, 1GB RAM, OS X 10.2.6). None of us have any experience with Macs but for various reasons we need to have one around for development. In any case, we've installed fink, all the Apple Developer Tools and the Dec2002updater to gcc 3.3. We're now trying to compile R 1.7.1 without too much success. First we had to get g77, which turned out to

Is there any effective way to get distinct geometric plotting symbols and colors for plots involving more than 25 groups? Thanks. Dr. Marc R. Feldesman Professor and Chairman Emeritus Anthropology Department - Portland State University email: feldesmanm at pdx.edu email: feldesman at attglobal.net fax: 503-725-3905 "Don't knock on my door if you don't know my

I've been using the package rpart with R 1.3.0 for Windows to produce simple classification trees for some measurement data from paleontological specimens. Both the rpart documentation and the output confirm that the program produces splits on continuous data that leave "holes" in the data. It is probably of little practical importance, but is there a reason why the binary

It may be my lack of unerstanding, but round() seems to me to give inconsistent results when rounding 5s as in the following examples? > round(1.45, 1) [1] 1.4 # OK > round(2.45, 1) [1] 2.5 # shouldn't this be 2.4? > round(1.05, 1) [1] 1.1 # 1.0 ? and signif(): > signif(2.445, 3) [1] 2.44 # OK > signif(3.445, 3) [1]

I just downloaded version 1.0.0 and several binary libraries (VR, rpart, norm, stataread) - WinNT version. I then converted a file from Stata 6.0 to R format by using the stataread library. The file converts perfectly and I was able to use the VR function lda on the dataframe without difficulty. I then tried to use the same dataframe with RPART. The model statement:

I ran across this error the other day while using lm(). I confess that I haven't used it for awhile and haven't been tracking the changes between versions of R. However, the piece of code below is a tiny modification of the example in the help file for "lm". I just separated the commands apart for clarity. A similar piece comes from the help file for

What is the generally accepted way to put certain math symbols into plain text email? For example, how does one convey the "is exactly equal to", "is approximately equal to", and "delta" symbols in a standard text-based (e.g. Courier) font? Dr. Marc R. Feldesman email: feldesmanm at pdx.edu email: feldesman at attglobal.net fax: 503-725-3905

I'm running a four-group, 15-variable discriminant analysis using the MASS function lda(). Discriminant functions 1 and 2 explain about 93% of the variance. I would like to plot the group scatters in a single scatterplot, identify each group's centroid, and encircle the group scatter with a 90% bivariate confidence ellipse. I can do this for each group on a separate plot, but I

I've created a bunch of postscript trees (post.rpart), which I subsequently edit in Adobe Acrobat 4.05 (I need additional labelling that isn't easy to add with R). After editing the labels and annotations using Acrobat, I then export the file to Adobe's .eps format so I can insert the picture into a Microsoft Word 2000 document. The .pdf file distilled from the .ps file is

I frequently get data sets with cryptically-named variables. The datasets are more useful to me with informative variable names. I know that I can rename variables using the following command: dimname(dataset[[2]][index.of.variable.to.be.renamed]<-new.variable.name If I want to do this inside a function (say something I call RenameCol) what is the best way to communicate the

At the risk of being flamed for mortal stupidity, I'm trying to figure out what could have possibly changed (at my end almost certainly) that make Brian Ripley's posts (in particular) not show up on my mail server (at least not on the one where I receive my email). All my email comes to a central university server from which it is forwarded to several different places where I can get

Sorry for the off-topic post, but there is such a wealth of knowledge here that I thought someone might have suggestions. Geoff MacLachlan and David Peel have a program - EMMIX - available for mixture modelling. It is only available as FORTRAN source code and is "downloadable" from Geoff's site. The code is reputed to run on Unix machines and is compilable according to

In my research area, researchers are very stingy about sharing data. In fact, they are frequently downright secretive about these morsels. Typically, we get fed a diet of summary statistics and the assurance that the data are *normal* without any necessary documentation that they really are. With that as background and assuming that the data really are normal, is there any way in R (or any

Before I reinvent the wheel, I have need for a relatively straightforward crosstabulation (2 x n) function. I know that R has table(), ftable(), xtabs(), and summary(xtabs()), but none of these produce a fully "tricked" out cross-tabulation with marginal totals, expected cell frequencies, and an array of statistics about the contingency table. Is there a more complete (something

Forgive what may seem to be a trivial question/problem. Below is some simple R 1.2.1(Windows) code with output. > summary(mammals, digits=10) Name Body.Weight Brain.Weight Red Fox :1 Min. : 3.0 Min. : 26.0 Pig :1 1st Qu.: 35.5 1st Qu.: 138.5 Man :1 Median : 100.0 Median : 406.0 Kangaroo:1 Mean : 761.2 Mean :1000.0 Jaguar :1 3rd

A week or so ago, I reported a problem on my new Windows XP box getting R 1.4.1 and R 1.5.0 (development from BDR's site) to save the .RData file upon program exit. Specifically, either clicking on the "X" in the GUI or invoking q() from the command line produced the following error: Error in save.image(name) : image could not be renamed and is left in .RDataTmp1 After some