similar to: linear regression: evaluating the result Q

On Thu, 16 Sep 2004, RenE J.V. Bertin wrote: > Dear all, > > A few quick questions about interpreting and evaluating the results of > linear regressions, to which I hope equally quick answers are possible. > > 1) The summary.lm method prints the R and R^2 correlation coefficients > (something reviewers like to see). It works on glm objects and (after > tweaking it to

You could use cut. The key calculation would be: w <- .05; eps <- 1e-5 breakpoints <- seq(min(kk), max(kk), .05) breakpoints <- floor( (breakpoints + (w/2) + eps) / w) * w values <- cut(kk, c(breakpoints, Inf), right = FALSE) values <- ordered(values) If you don't like the labels produced add lab = breakpoints as a cut arg. On 11/10/05, RenE J.V. Bertin

Concerns: R 1.5.0 gui version, Windows (downloaded binary) and Linux (installed from sources). # Load the data from the attached file: kk<-read.table("__filename__", header=1) # attach the data: attach(kk) Snr<-factor(Snr) # fool around with a call to anova.glm(): anova.glm( aov( nFD~Type+size+Modality+Error(Snr/(Type+size+Modality)) ) ) # Error: object nFD not found # Well, I

RenE J.V. Bertin wrote: > Hello, and (somewhat belated) best wishes for 2005. > > Can one order not to draw outliers in bwplot, or at least exclude them from the vertical axis scaling? If so, how (or what doc do I need to consult)? > The options that have this effect in boxplot() do not appear to have any effect with bwplot (although outline=FALSE in boxplot does *not* change the

Rene, Look at ?format. Sean On Sep 17, 2004, at 9:21 AM, RenE J.V. Bertin wrote: > Hello, > > I can't seem to find the way to modify the precision with which > paste() prints its floating point numbers, more precisely the number > of decimal digits printed. This is apparently not controlled by > options( digits= ), and there is no appropriate argument to paste() >

[I hope all of you had some good holidays/vacation!] My current flabbergaster: ## a dummy factor > size<- rep( c('short', 'long'), 10 ) ## take a subset: > subset( size, size!='short') [1] "long" "long" "long" "long" "long" "long" "long" "long" "long" "long" ##

Dear all, I am stuck at applying loop function for creating separated plots. I have coding like below: dataset.table <- table(data.frame(var1=c(1,2,3,1,2,3,1),colour=c("a","b","c","c","a","b","b") )) kk = function(f) { ls=as.character(f) pie(dataset.table[ls,],main=ls)

Dear all, I have a question about how to load data or (entering data )to each cell of a rectangle created by rect . e.g. I have a matrix rbind(1:2,1:2) I have created a 2x2 rectangle by using: a<-0:1/10 b<-0:1/10 kk<-expand.grid(a,b) plot.new() rect(kk[, 1], kk[, 2], kk[, 1] + .1,kk[, 2] + .1) so how do we put the value of rbind(1:2,1:2) into the relevant

&gt;From: Patrick Connolly &lt;p.connolly@hortresearch.co.nz&gt; &gt;To: &quot;RenE J.V. Bertin&quot; &lt;rjvbertin@hotmail.com&gt; &gt;Subject: Re: [R] changing (core) function argument defaults? &gt;Date: Thu, 18 Nov 2004 11:43:10 +1300 &gt; &gt;On Wed, 20-Oct-2004 at 07:48PM +0200, RenE J.V. Bertin wrote: &gt; &gt;|&gt; Hello,

&gt;From: Patrick Connolly &lt;p.connolly@hortresearch.co.nz&gt; &gt;To: &quot;RenE J.V. Bertin&quot; &lt;rjvbertin@hotmail.com&gt; &gt;Subject: Re: [R] changing (core) function argument defaults? &gt;Date: Thu, 18 Nov 2004 11:43:10 +1300 &gt; &gt;On Wed, 20-Oct-2004 at 07:48PM +0200, RenE J.V. Bertin wrote: &gt; &gt;|&gt; Hello,

RenE J.V. Bertin wrote: > I find myself doing lots of tests like > > >>subset( data, symptoms=='a' | symptoms=='e' | symptoms=='z' .... ) > > > with symptoms one of the factors contained in the data frame. > > and I wonder if there is not an existing operator or function which implements this sort of repeated conditional in a more

It doesn't print anything: the summary.aov (or summary.aovlist) print method does. ?summary.aov tells you the structure of the objects they return. On Tue, 15 Feb 2005, RenE J.V. Bertin wrote: > I'd like to annotate a plot with the output of summary(aov(model)), > ideally just with the significant effects. I don't find a means to > redirect what that command prints into

It's in the FAQ, Q7.12. On Wed, 19 Nov 2003, RenE J.V. Bertin wrote: > After converting a numeric variable into a factor, is there a way to convert it back to the original values? as.double() doesn't do that correctly, for evident reasons (I guess) and as shown below. -- Brian D. Ripley, ripley at stats.ox.ac.uk Professor of Applied Statistics,

This may be of interest: http://www.ijs.si/software/snprintf/ It looks like this version may well be more complete and conform the standards than the version that comes with R. BTW: I am currently patching unix/sys_std.c and modules/gtkconsole.c such that they don't store lines in the history that are identical to the previous line. Is there any interest in posting those patches here? RenE

Starting html help in the current version of R has a very annoying side-effect. It indiscriminantly removes $HOME/.R, and replaces it with a virgin copy. I discovered that when all of a sudden I got complaints about my startup "library" not being found. Below is a modified version of the script that doesn't do this. It is not perfect yet (it shouldn't try to recreate links

Take a look at package mgcv. Hope this helps. --Matt -----Original Message----- From: RenE J.V. Bertin [mailto:rjvbertin at despammed.com] Sent: Thursday, February 27, 2003 1:39 PM To: r-help at stat.math.ethz.ch Subject: [R] multidimensional function fitting Hello, I have been looking around for how to perform a multidimensional, arbitrary function fit (in any case non-linear; more below),

Hi r-users,   I would like to extract the data that match.  Attached is my data: I'm interested in matchind the value in column 'intg' with value in column 'rand_no' > cbind(z=z,intg=dd,rand_no = rr)             z  intg rand_no    [1,]  0.00 0.000   0.001    [2,]  0.01 0.000   0.002    [3,]  0.02 0.000   0.002    [4,]  0.03 0.000   0.003    [5,]  0.04 0.000   0.003    [6,] 

Let's say I have a within-subject experiment with 2 observables, obs1 and ob2 and 2 independent factors, fac1 and fac2. I can do summary( aov( obs1~fac1*fac2 + Error(Subject/(fac1*fac2)) ) ) summary( aov( obs2~fac1*fac2 + Error(Subject/(fac1*fac2)) ) ) to test the 2 observables separately. > summary( fit<-manova( cbind(obs1,obs2)~fac1*fac2 + Error(Subject/(fac1*fac2)) ) ) gives

On 6/23/05, RenE J.V. Bertin <rjvbertin at gmail.com> wrote: > Hello, > > I was just having a look at the aov function source code, and see that when the model used does not have an Error term, Helmert contrasts are imposed: > > if (is.null(indError)) { > ... > } > else { > opcons <- options("contrasts") >

I commend you to (a) the recent article by Doug Bates on "Fitting nonlinear mixed models in R" pp. 27-30 in the latest issue of "R News" available from "www.r-project.org" -> Newsletter and (b) Doug's book with Pinheiro (2000) Mixed-Effects Models in S and S-PLUS (Springer). I suggest you try the same analysis using in "lmer", library(lme4), and