similar to: Plotting slowly

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,

Greetings! Soon I will begin teaching 2 courses two students who have never met R or SPLUS before. I'm just wondering if list members are aware of any on-line lecture notes about R or using R to teach statistics apart from the Venables & Smith notes? One drawback to R is its name, which is not very useful as a search string in internet search engines! Murray Jorgensen, Department of

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

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

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>

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

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

At 07:12 AM 10-10-00 +0100, Prof Brian D Ripley wrote: >On Tue, 10 Oct 2000, Murray Jorgensen wrote: > >> Excuse me everyone, but I don't have to teach this very often! >> >> Has anyone got some R code for doing adjusted treatment means and the >> recovery of inter-block information in the analysis of balanced incomplete >> block designs? > >Do you

It is not uncommon to want to coarsen a factor by grouping levels together. I have found one way to do this in R: > sites [1] F A A D A A B F C F A D E E D C F A E D F C E D E F F D B C Levels: A B C D E F > regions <- list(I = c("A","B","C"), II = "D", III = c("E","F")) > library(Epi) > region <-

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

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

This is somewhat off-topic but I think that an answer may help other users of R-help. Thunderbird trys to help in the display of messages by "greying out" quoted text. However when reading r-help in digest form it gets thoroughly confused and usually ends up greying out the fresh text in a message. [I'm using Windows XP]. Does anyone know how to turn off this Thunderbird

I am wondering if stepAIC in the MASS library may be used for model selection in an overdispersed Poisson situation. What I thought of doing was to get an estimate of the overdispersion parameter phi from fitting a model with all or most of the available predictors (we have a large number of observations so this should not be problematical) and then use stepAIC with scale = phi. Should this

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

I had an error message while running a macro from Yudi Pawitan's web site: > source("ex2-13.r") Error in parse(file, n, text, prompt) : syntax error on line 2 Inspecting ex2-13.r I found that the error was generated by another source() command. Clearly R does not like nested source()s, which is fair enough when you think about it. Still it's something that you might want

We have a choice when calculating the Huber location estimate: > set.seed(221205) > y <- 7 + 3*rt(30,1) > library(MASS) > huber(y)$mu [1] 5.9117 > coefficients(rlm(y~1)) (Intercept) 5.9204 I was surprised to get two different results. The function huber() works directly with the definition whereas rlm() uses iteratively reweighted least squares. My surprise is

Consider the following output [R2.2.0; Windows XP] > set.seed(160706) > X <- matrix(rnorm(40),nrow=10,ncol=4) > Xpc <- princomp(X,cor=FALSE) > summary(Xpc,loadings=TRUE, cutoff=0) Importance of components: Comp.1 Comp.2 Comp.3 Comp.4 Standard deviation 1.2268300 0.9690865 0.7918504 0.55295970 Proportion of Variance 0.4456907 0.2780929