similar to: Extract psuedo model matrix from nls?

Hi, I have found a minor problem with leaps(). In 1.3.1 under Windows 2000 I seem to only be able to obtain values for one statistic at a time. That is choosing method=c("Cp","adjr2","r2") just gives Cp values. To mimic the output of Minitab's MTB > BReg 'Fertility' 'Agriculture'-'Infant.Mortality' ; SUBC> NVars 1 5; SUBC>

Hello R Folks, I am new to R. I have been struggling to overlay a barchart with a xyplot together on one plot but did not get this worked out. Any help and idea are greatly appreciated. I attached R scripts for barchart and xyplot below and also data I used. What I am trying to do is just to put the barchart and xyplot together on one plot. Huapeng <<dispersal_infestation.csv>>

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

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

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

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

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 have just installed R 2.11.1 on my XP laptop. I like html help for browsing but text help for on-the-fly look-ups. I was a bit surprised when I was asked to choose between them during the installation. I chose text, thinking I could fix the html help later, which is what I am trying to do now. Now when I ask for html help my browser goes to 'http://-ip-number-/doc/html/index.html'

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 <-

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

I assigned a class the first problem in Pinheiro & Bates, which uses the data set PBIB from the SASmixed package. I have recently downloaded 2.0.1 and its associated packages. On trying library(SASmixed) data(PBIB) library(nlme) plot(PBIB) I get a warning message Warning message: replacing previous import: coef in: namespaceImportFrom(self, asNamespace(ns)) after library(nlme) and 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

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

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

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 want to extra the part of the formula not including the response variable from an lm object. For example if the lm object ABx.lm was created by the call ABx.lm <- lm( y ~ A + B + x, ...) Then ACx.lm is saved as part of a workspace. I wish to extract "~ A + B + x". Later in my code I will fit another linear model of the form z ~ A + B + x for some other response variable z. I

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