similar to: sum overflow (PR#1091)

Full_Name: Version: 1.0.0 OS: linux Submission from: (NULL) (193.62.250.209) ?par lists and describes xlog and ylog, though these are obsolete. It does not list log. I found out about log from ?plot.defaults--so that help is OK. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send

Full_Name: Bill Simpson Version: 65.1 OS: linux Submission from: (NULL) (193.62.250.209) Try this code as separate lines entered interactively, then try doit() doit<-function() { x<-seq(1,10) y1<-x+rnorm(10,1,1.5) y2<-x+rnorm(10,1,1) t.test(x,y1,paired=TRUE) t.test(x,y2,paired=TRUE) } doit() apparently executes only the last of a series of t.test()s. Maybe this is no bug,

Full_Name: Bill Simpson Version: 0.64.1 OS: linux Submission from: (NULL) (193.62.250.209) Two problems with dev.print help. 1. Under Examples: dev.print(width=6, height=6, horizontal=F) ^ FALSE 2. dev.print help does not describe any of its parameters (e.g. height or width). Not described on the other dev.xxx pages either

Full_Name: Bill Simpson Version: 65.1 OS: Linux Redhat 6.1 Submission from: (NULL) (193.62.250.209) Try this: #default plot symbols and lettering are too small, need to scale up par(cex=2,mex=.7) par(mar=c(5,5,1,1)) spdiff<-c(1,2,3,4,5) dpdet<-c(1,2,3,4,5)/10 dpsp<-c(2,3,4,5,6)/10 dpdir<-c(2,4,6,8,10)/10 plot(spdiff,dpdet,pch=15,ylim=c(0,max(dpdet,dpsp,dpdir)),xlab="Speed

I use AfterStep on Linux. I made an R.xpm file (attached) and put this icon in the "wharf". To invoke R I click on the R icon. I did not find an offical R.xpm, and so I am submitting this one for your collective consideration.... The idea behind the icon is that it looks like a scatterplot, which is "statistical". My main beefs with my R.xpm are that it doesn't have a

I have not really used lm before and I was hoping for some help on a simple problem. Here is a toy version of the problem I want to solve. y x grp -.9 1 a -.8 2 a -.7 3 a -.7 1.5 b -.5 2.5 b -.3 3.5 b -.19 2.7 c -.11 3.7 c -.41 4.7 c I want to fit a model that has one y-intercept and three slopes, one for

I was wondering if anyone out there has created a series of images (e.g. jpegs) using R, then animated them on a web page. I have looked around a bit and it seems fairly complicated. One approach that seems sensible is to use a java script that displays the list of images. I have only used html on web pages before so I don't know how to use java... Ideally the final result is easily ported to

There were some questions about hist() a couple of days ago which triggered this post. My question/suggestion is about the y-axis in hist. There are reasons to prefer making the y-axis density=relative frequency/bin width. One reason is that the height of the plot does not depend on the bin width; another is that if your histogram is in density then you can easily superimpose a smooth theoretical

I just installed 99.0a, and I can't set mar and mgp: > par(mar(2,2,.1,.1)) Error in par(mar(2, 2, .1, .1)) : couldn't find function "mar" I had the same happen with mgp. Are these bugs or a problem in my installation (everything else seems OK)? Is R core going to kill mar and mgp? If so, how should I fix the huge margins and huge space between axis title and axis? Try this

The problem is illustrated below: line<-function(x,y) { fit<-lm(y~x) fit } func<-function() { x<-c(1,2,3,4) y<-c(1.1,2,3,4) for(i in 1:2) { fit<-line(x,y) summary(fit) } } Why don't I get two printed summaries when I run func()? How to make it work? (In reality I will be getting different summaries of different data sets using this loop) Thanks very much for any

Dear addresses, I need perform a batch of 10 000 simulations for each of 4 options considered. (The idea is to obtain the parameter estimates in a heteroskedastic linear regression model - with additive or mixed heteroskedasticity - via the Kenward-Roger small-sample adjusted covariance matrix of disturbances). For this purpose I wrote an R program which would capture all possible options (true

A while ago there was a thread on graphics. I complained that the plots produced by dev.print had symbols and fonts that were too small. I said I had been using par(cex=2), but the advice was to use pointsize. I have tried ps, is that what was meant? par(ps=40) x<-rnorm(100) y<-rnorm(100) dev.print(file="~/junk.ps", horizontal=FALSE) No matter how big I make ps (40,60...), the

> From: David Smith [mailto:dsmith@insightful.com] >> From: Prof Brian Ripley >> >> If you use integers you need to be aware of the consequences. It's a >> feature not a bug. > > Perhaps, but maybe a more useful feature would be to signal to the user when > such an overflow occurs? Sv4 does this by returning NA for overflow integer > results: > >

I found out the other day that crossprod() will take a single matrix argument; crossprod(x) notionally returns crossprod(x,x). The two forms do not return identical matrices: x <- matrix(rnorm(3000000),ncol=3) M1 <- crossprod(x) M2 <- crossprod(x,x) R> max(abs(M1-M2)) [1] 1.932494e-08 But what really surprised me is that crossprod(x) is slower than crossprod(x,x): R>

I was just playing around with the R-streams package, reading in some data from an old experiment we did here, and was again amazed by the flexibility of the R environment. The eaze with wich I was able to generate simple plots of my EEG data made me wonder if someone tried to implement an ERP package. For the non-cognitive scientists ou there: EEG is electrical activity measured from the scalp

This is probably a trivial question, but I did not see it in the FAQs. Perhaps I simply need to be pointed to some URLs. In any case, I have some sampled data that has peaks, and I would like to extract peak height, location, and width, according to almost any statistical model. Gaussian would seem to make the most sense. There can also be "steps" increasing the amplitude over a

Hi everyone, I do a lot of work with large variance matrices, and I like to use "crossprod" for speed and to keep everything symmetric, i.e. I often compute "crossprod(Q %*% t(A))" for "A %*% Sigma %*% t(A)", where "Sigma" decomposes as "t(Q) %*% Q". I notice in the code that "crossprod", current definition > crossprod function (x,

The following is at least as much out of intellectual curiosity as for practical reasons. On reviewing some code written by novices to R, I came across: crossprod(x, y)[1,1] I thought, "That isn't a very S way of saying that, I wonder what the penalty is for using 'crossprod'." To my surprise the penalty was substantially negative. Handily the client had S-PLUS as

Hi I have a square matrix Ainv of size N-by-N where N ~ 1000 I have a rectangular matrix H of size N by n where n ~ 4. I have a vector d of length N. I need X = solve(t(H) %*% Ainv %*% H) %*% t(H) %*% Ainv %*% d and H %*% X. It is possible to rewrite X in the recommended crossprod way: X <- solve(quad.form(Ainv, H), crossprod(crossprod(Ainv, H), d)) where quad.form() is a little

Dear R-users, I found a strange problem working with products of two matrices, say: a <- A[i, ] ; crossprod(a) where i is a set of integers selecting rows. When i is empty the result is in a sense random. After some trials the right answer (a matrix of zeros) appears. --------------- Illustration -------------------- R : Copyright 2003, The R Development Core Team Version 1.8.0