similar to: Resources for teaching R

I'm running R 1.2.2 under windows 98 on a Pentium 133 laptop. I can't seem to retrieve the package MASS data sets: > library(MASS) > data(wtloss) Warning message: Data set `wtloss' not found in: data(wtloss) > data(abbey) Warning message: Data set `abbey' not found in: data(abbey) And yet all the .rda files for the MASS datasets are in D:\Program

How about: > dim [1] 3 1 4 1 5 > N <- length(dim) > one <- rep(c(3,4),N) > two <- c(rep(1,N),dim) > three <- rep(1:N,rep(2,N))+N*rep(0:1,N) > rep(one,two[three]) [1] 3 4 4 4 3 4 3 4 4 4 4 3 4 3 4 4 4 4 4 ---------------------- Bendix Carstensen Senior Statistician Steno Diabetes Centre Niels Steensens Vej 2 DK-2820 Gentofte Denmark tel: +45 44 43 87 38 mob: +45 28

Hi all, has anyone written a function to do "best subsets" regression similar to the Minitab command? Regards, Murray Jorgensen Murray Jorgensen, Department of Statistics, U of Waikato, Hamilton, NZ -----[+64-7-838-4773]---------------------------[maj at waikato.ac.nz]----- "Doubt everything or believe everything:these are two equally convenient strategies. With either we

Please excuse this request from a beginner. I'm teaching an introductory module on experimental design and I want to illustrate the idea of tests based on the randomization distribution. If anyone has written any R code to do a randomization test in a particular example I'd be very grateful if you could show me your code. Murray Jorgensen Murray Jorgensen, Department of Statistics,

Some older members of this list will remember the strange pleasure of seeing a pattern slowly emerge as points were laboriously added to a scatterplot on graph paper. A colleague (Harold Henderson, in fact) recently pointed out to me that there is some quite interesting structure in the abrasion loss data set of O. L. Davies (reprinted in the book by Hand et al) if you consider the order of the

Forgive me, but while I find the documentation for initially installing R to be clear, I'm not so happy about updating. I want to update from R 1.2.1 to R 1.2.2 (mainly so I can get the debugged version of pictex() ). Now I have downloaded the base zip files, say to Z:\Program Files and my existing installation of R 1.2.1 is sitting in Z:\Program Files\rw1021. Running rwinst.exe I need to

Greetings all I promised a summary of the responses that I got to my question: "Next year I will be teaching a third year course in applied statistics about 1/3 of which is multivariate statistics. I would be interested in hearing experiences from those who have taught multivariate statistics using R. Especially I am interested in the textbook that you used or recommended." There

Bother! This cold has made me accident-prone. I meant to hit Reply-all. Clarification below. -------- Original Message -------- Subject: Re: [R] Parameterization puzzle Date: Fri, 21 Jul 2006 19:10:03 +1200 From: Murray Jorgensen <maj at waikato.ac.nz> To: Prof Brian Ripley <ripley at stats.ox.ac.uk> References: <44C063E5.3020703 at waikato.ac.nz>

G'day list! I'm thinking about programming likelihood and score intervals for generalized linear models in R based on the paper "On the computation of likelihood ratio and score test based confidence intervals in generalized linear models" by Juha Alho (1992) (Statistics in Medicine, 11, 923-930). Being lazy, I thought that I would ask if anyone else on the list has

I can ask my question using and example from Chapter 1 of Pinheiro & Bates. > # 1.4 An Analysis of Covariance Model > > OrthoFem <- Orthodont[ Orthodont$Sex == "Female", ] > fm1OrthF <- + lme( distance ~ age, data = OrthoFem, random = ~ 1 | Subject ) > summary( fm1OrthF ) Linear mixed-effects model fit by REML Data: OrthoFem AIC BIC

Having just update to R 2.6.2 on my old Windows laptop I notice that the number of packages is growing exponentially and my usual approach of get-em-all may not be viable much longer. Has any thought been given to dividing "contributed" binaries into a recommended set, perhaps a couple of hundred, and the remained. That way one could install the recommended ones routinely and add in

How do you stop R from putting up a dialog box when you quit Rgui? (I use Windows and I never save workspaces that way) Murray -- Dr Murray Jorgensen http://www.stats.waikato.ac.nz/Staff/maj.html Department of Statistics, University of Waikato, Hamilton, New Zealand Email: maj at waikato.ac.nz Fax 7 838 4155 Phone +64 7 838 4773 wk +64 7 849 6486 home

I am exploring the result of clustering a large multivariate data set into a number of groups, represented, say, by a factor G. I wrote a function to see how categorical variables vary between groups: > ddisp <- function(dvar) { + csqt <- chisq.test(G,dvar) + print(csqt$statistic) + print(csqt$observed) + print(round(csqt$expected)) + round(csqt$residuals) + } > > x

If rb.lm is an lm-object, I can access the error mean square as s2 <- sum(rb.lm$residuals^2)/rb.lm$df.residual This seems a bit like hard work for such a commonly wanted quantity. Is there a better way to do this? Murray Jorgensen Dr Murray Jorgensen http://www.stats.waikato.ac.nz/Staff/maj.html Department of Statistics, University of Waikato, Hamilton, New Zealand Email: maj at

I got a shock a few days ago when I accidentally visited www.r-project.com . I thought that the r-project site had been hacked until I realised my mistake. There is also a site www.r-project.net. Both of these sites appear to be Japanese. Does anyone know anything about them? I suppose that it is not unusual for names close to those of popular sites to be used. It is good that they use a

I forgot to mention that I am using Windows XP. -------- Original Message -------- Subject: Pasting data into scan() Date: Tue, 02 May 2006 11:55:03 +1200 From: Murray Jorgensen <maj at stats.waikato.ac.nz> To: r-help at stat.math.ethz.ch The file TENSILE.DAT from the Hand et al "Handbook of Small Data Sets" looks like this: [...] -- Dr Murray Jorgensen

I wanted a sort of matrix product of an array and a matrix. As there does not seem to be any array multiplication apart from outer() I proceeded as follows: lambda <- array(0, c(n,m,d)) # stuff omitted # zed is an n by m matrix # # \lamb.star_{ik} lamb.star <- matrix(0, nrow=n, ncol=d) for (i in 1:n) { for (k in 1:d) { for (j in 1:m) { lamb.star[i,k] = lamb.star[i,k] +

In one saved workspace I have the results of a simulation experiment stored as an array "resarray". > dim(resarray) [1] 10 6 500 3 In another workspace I have a similar array from another run of the simulation. I want to combine the two arrays into a single array of dimensions 10, 6, 1000, 3 What's the best way to do this? Murray Jorgensen Dr Murray Jorgensen

I want to interlace two vectors. This I can do: > x <- 1:4 > z <- x+0.5 > as.vector(t(cbind(x,z))) [1] 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 but this seems rather inelegant. Any suggestions? Murray -- Dr Murray Jorgensen http://www.stats.waikato.ac.nz/Staff/maj.html Department of Statistics, University of Waikato, Hamilton, New Zealand Email: maj at waikato.ac.nz

Hi all, I have just found out that the machine learning group in our Faculty has a lot of spare capacity on their FreeNX servers. I do not know a lot about these beasts but I understand that they are a free version of something produced by a firm called "NoMachine". They are designed for executing parallel algorithms and I thought that they might be of use in a project of mine