similar to: Extracting formula from an lm object

Displaying 20 results from an estimated 3000 matches similar to: "Extracting formula from an lm object"

2010 Jun 14
2
Html help
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'
2010 Jul 29
1
Sweaving quotes
The significance code line to summary() applied to an lm() fitted model object is Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1 The corresponding line in the LaTeX source produced by Sweave is Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1 which looks the same in my email (Thunderbird on a Vista machine), but when I look at the file in WinEdt the quotes
2010 Jul 27
4
Sweave and scan()
I am introducing the scan() function to my class. Consider the following file (Scanexamp.Rnw ) \documentclass[12pt]{article} \begin{document} <<>>= height = scan() 64 62 66 65 62 69 72 72 70 part = scan(what = character(0)) "Soprano" "Soprano" "Soprano" "Alto" "Alto" "Tenor" "Tenor" "Bass"
2006 Jul 21
0
[Fwd: Re: Parameterization puzzle]
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>
2008 Aug 26
2
lattice plotting character woes
The following reproducable code shows the setting of my problem: set.seed(260808) n = 50 x = rnorm(n) y = rnorm(n) z = ceiling(runif(n,0,4)) g = runif(n,0,6) G = factor(ceiling(g)) xyplot(y ~ x | G) plsy <- trellis.par.get("plot.symbol") plsy$pch = z trellis.par.set("plot.symbol",plsy) xyplot(y ~ x | G) plsy$pch = as.character(z)
2008 Apr 28
2
F values from a Repeated Measures aov
Hi Folks, I have repeated measures for data on association time (under 2 acoustic condtions) in male and female frogs as they grow to adulthood (6 timepoints). Thus, two within-subject variables (Acoustic Condition: 2 levels, Timepoint: 6 levels) and one between-subject variable (Sex:male or female). I am pretty sure my distributions depart from normality but I would first like to simply run a
2003 Jan 12
1
likelihood and score interval estimates for glms
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
2006 Jun 05
1
Extracting Variance components
I can ask my question using and example from Chapter 1 of Pinheiro & Bates. > # 1.4 An Analysis of Covariance Model > > OrthoFem <- Orthodont[ Orthodont$Sex == "Female", ] > fm1OrthF <- + lme( distance ~ age, data = OrthoFem, random = ~ 1 | Subject ) > summary( fm1OrthF ) Linear mixed-effects model fit by REML Data: OrthoFem AIC BIC
2008 Mar 02
2
Recommended Packages
Having just update to R 2.6.2 on my old Windows laptop I notice that the number of packages is growing exponentially and my usual approach of get-em-all may not be viable much longer. Has any thought been given to dividing "contributed" binaries into a recommended set, perhaps a couple of hundred, and the remained. That way one could install the recommended ones routinely and add in
2006 Nov 13
2
A printing "macro"
I am exploring the result of clustering a large multivariate data set into a number of groups, represented, say, by a factor G. I wrote a function to see how categorical variables vary between groups: > ddisp <- function(dvar) { + csqt <- chisq.test(G,dvar) + print(csqt$statistic) + print(csqt$observed) + print(round(csqt$expected)) + round(csqt$residuals) + } > > x
2000 Oct 11
0
Balanced incomplete block analysis
At 07:12 AM 10-10-00 +0100, Prof Brian D Ripley wrote: >On Tue, 10 Oct 2000, Murray Jorgensen wrote: > >> Excuse me everyone, but I don't have to teach this very often! >> >> Has anyone got some R code for doing adjusted treatment means and the >> recovery of inter-block information in the analysis of balanced incomplete >> block designs? > >Do you
2001 Sep 18
2
Error mean square
If rb.lm is an lm-object, I can access the error mean square as s2 <- sum(rb.lm$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
2002 Oct 28
2
Combining simulation results
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
2005 Sep 08
1
Coarsening Factors
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 <-
2009 Nov 25
2
R or C++ on FreeNX servers
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
2005 Apr 05
1
nlme & SASmixed in 2.0.1
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
2007 Jul 09
2
ANOVA: Does a Between-Subjects Factor belong in the Error Term?
I am executing a Repeated Measures Analysis of Variance with 1 DV (LOCOMOTOR RESPONSE), 2 Within-Subjects Factors (AGE, ACOUSTIC CONDITION), and 1 Between-Subjects Factor (SEX). Does anyone know whether the between-subjects factor (SEX) belongs in the Error Term of the aov or not? And if it does belong, where in the Error Term does it go? The 3 possible scenarios are listed below: e.g., 1.
2006 May 02
0
Pasting data into scan() - oops!
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
2000 Nov 01
0
Loop elimination question
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
2004 Feb 05
2
Sweave problem
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