similar to: R != S-Plus

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:

At the risk of starting a holy war, I'd like opinions on the "best" current Linux distribution to run "out of box" with current versions of R. I note rpms for various versions of RedHat, SUSE, Mandrake, and Debian. I've had experience with RH 7.1 & 7.2 and it hasn't been entirely pretty. I understand that 7.3 is a bit "better", but have also

Sorry for the uninformative subject. The following piece of code gives different output in S-Plus (2K & 6) vs R 1.2.1 (Win) apply(apehum[,6:15], 2, function(x) which(is.na(x))) S-Plus results: > apply(apehum[,6:15], 2, function(x) which(is.na(x))) $latsupri: numeric(0) $medepico: numeric(0) $pdhtcapi: numeric(0) $mlhtcapi: numeric(0) $aphttroc: [1] 151 152 $mlhttroc: numeric(0)

I'd like to give a copy of an R package to someone using S-PLUS. It doesn't just run as-is, it'll need changes. Has anyone written any general guidelines on ways to port in that direction? Duncan Murdoch

I'm not really sure this is the place to raise this, but here goes anyway. I've downloaded the 1.4.0 recommended package sources R-1.4.0-recommended.tgz multiple times from the main CRAN site. The sources have arrived corrupted each time (from multiple computers BTW). If I download the same file from the UCLA or University of Bristol mirror, I also get corrupt archive files. On the

I'm trying to adapt some S-Plus scripts to run in R (1.2.2, Windows). In one of these scripts, I've bootstrapped the prediction success rate under the discriminant function (lda). The bootstrap() functions are proprietary to S-Plus and there aren't exact equivalents in R. The closest is Canty's library boot based on the Davidson and Hinkley book. Unfortunately, I

Hi All, I would like to use anonymous cvs, but it appears not to be working (again?). There was a discussion back in Jan-Feb about whether to continue supporting it, but it seemed that Tony Rossini got it working and the discussion left off there. Did someone decide to disable it, or is it just not working properly? Here's the details: $ cvs -d

Hi Folks, Sorry to raise what has probably been discussed before, but I an repeatedly struck by the comparative slowness of S-plus for Windows compared with R for Linux when doing much the same thing. I don't have a direct comparison, because they're not running on the same machine; but machine W has a faster CPU and more RAM than machine L, yet S-plus on W seems to take longer by quite

Dear R users, I ran into this curious problem: > d <- rnorm(100) > d.density <- density(d) > sum( d.density$x * d.density$y) [1] 2.517502 Admittedly the method of computing the mass under the density curve at line 3 is crude. But 2.5 is pretty far from 1, the value it should be. I tried a few other dataset and got similar result. Am I missing something obvious? Or is the return

As a user of only R, I don't use much of the potential of ESS and Emacs. Without entering a religious feud, is there any reason I should use XEmacs rather than my current GNU Emacs? (I looked on the XEmacs site, but I didn't understand the programming issues they were talking about (over my head).) Martin Henry H. Stevens, Assistant Professor 338 Pearson Hall Botany Department Miami

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

Dear R experts, Sorry, I am resending this, since I have not received this mail myself for the past 5 hours. I saw a similar question dated July 2. But there is no answer to it. Does anybody have a solution to it? I am using window NT, and the R version is 1.5.1, the SJava package is the binary version SJavaWin_0.62-8.zip. Here are the error message: > library(SJava) > .JavaInit()

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 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

Hi Folks, I'm currently looking at missing data/imputation methods (including multiple imputation). S-Plus has a "missing data library". What similar resources are available within R? Or does one roll one's own? Best wishes to all, Ted. -------------------------------------------------------------------- E-Mail: (Ted Harding) <Ted.Harding at nessie.mcc.ac.uk>

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:

Hello everyone, Thanks to all who offered suggestions after my initial query to the list. I've been busy trying to absorb the docs as fast as possible, but this little thing has me stumped for the moment. I'm creating a random sample of 100 item and saving it to a vector named 'iq'. I'd like to create a second vector (iq_prime, say) by adding 20 to each element of the

Hello everyone, Thanks to all who offered suggestions after my initial query to the list. I've been busy trying to absorb the docs as fast as possible, but this little thing has me stumped for the moment. I'm creating a random sample of 100 item and saving it to a vector named 'iq'. I'd like to create a second vector (iq_prime, say) by adding 20 to each element of the

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))) + ) >

Dear list members, I've had helpful feedback from a number of people, several of whom experienced some problems getting my XEmacs/ESS configuration files for Windows to work properly. I will, of course, make changes based on this feedback, but the following information may be of use in the interim: (1) It's clear that my instructions and installation procedure were insufficiently