similar to: likelihood and score interval estimates for glms

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 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

Greetings all. Any help with the following would be appreciated. I want to create a data frame for each file in a directory. The following code does not work but it may show what I am trying to do: carmakes <- c('BMW','Chrysler','Citroen','Fiat','Ford','Holden','Honda',

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

Well I don't know if anyone can help with this but it will be interesting to know if others have had the same problem. I can't start R at home on my laptop [ I'm using 1.8.1 under Windows XP]. When I click on the shortcut I get the usual Windows box for when an application needs to close. A couple of clicks down it displays the following: Error signature AppName: rgui.exe

I have just noticed that quite a few columns of a data frame that I am working on are numeric factors. For summary() purposes I want them to be vectors. I tried, for example > indx <- c(1:18,21:37,40,41) > i <- 0 > i <- i+1 > summary(as.vector(sflows1[indx[i]])) Length Class Mode min.pkt.sz 3000 factor numeric but this does not give the five-number

Does anyone else miss email-friendly character graphics such as the following example, produced using Minitab? Histogram of C6 N = 478 N* = 21 Each * represents 2 observation(s) Midpoint Count -12 16 ******** -11 53 *************************** -10 63 ******************************** -9 83

Suppose you fit a linear model > model.1 ~ lm(v1 ~ ..., data=myframe) and v2 is some other column of myframe typically not in the model. You will often want to try > plot(v2, model.1$residuals) but this will fail if there are NAs in the response v1 as model.1$residuals has length equal to the number of nonmissing values in v1. I suppose > plot(v2[!is.na(v1)],

Here is the file minimal.Snw: \documentclass[a4paper]{article} \title{R tips and tricks} \author{Murray Jorgensen} \usepackage{Sweave} \begin{document} \maketitle \section*{Entering data from a single variable} The following data are transformed tensile strength measurements on polyester fibres. They may be found on the file \texttt{TENSILE.DAT}. We may enter this data into R using the

I want to paste in the following numbers into a scan: 0.023 0.032 0.054 0.069 0.081 0.094 0.105 0.127 0.148 0.169 0.188 0.216 they are separated by tabs alone, unless my mailer has done something to the tabs. Now have a look at this: > scan() 1: 0.0230.0320.0540.0690.0810.094 1: 0.1050.1270.1480.1690.1880.216 Error in scan() : "scan" expected a real, got

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] +

Hi all, I have some email addresses that I would like to sort in reverse lexicographic order so that addresses from the same domain will be grouped together. How might that be done? 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

R is a function-oriented language and functions have the advantage that they control unintended side effects of computations on the workspace. Still, there are times when I am using R when I want to make a large number of changes to the worksheet repeatedly and where the easiest way seems to be to keep pasting in the same chunk of code, or to put it on a file and use

I found myself wanting to average a vector [vec] within each level of a factor [Fac], returning a vector of the same length as vec. After a while I realised that lm1 <- lm(vec ~ Fac) fitted(lm1) did what I want. But there must be another way to do this, and it would be good to be able to apply other functions than mean() in this way. Cheers, Murray -- Dr Murray Jorgensen

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

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

Consider the following analysis of a class experiment done as a Latin Square: > spinner <- gl(4,4,16,label=c("Murray","Angela","Shasha","Stephen")) > order <- gl(4,1,16) > treat <- scan() 1: 1 2 4 3 5: 4 3 1 2 9: 3 4 2 1 13: 2 1 3 4 17: Read 16 items > coin <-

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

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

Can some kind person point out my error here? I'm trying to set up a grid for a countour plot of a likelihood function. > u <- rnorm(20,9.5,2.5) > # sample of size 20 from N(9.5,2.5^2) > loglik <- function(th1,th2) { + n <- length(u) + -(n/2)*log(2*pi*th2^2)-0.5*sum((u-th1)^2/th2^2) + } > x <- seq(4.5,14.5,len=50) > y <- seq(0.5,6,len=50) > f <-