similar to: Installing contributed packages on MacOS X: Solved!

Hello, I'm using R 1.40 on MacOS X X.1.2 (installed via the fink package manager). To upgrade my installed packages, I tried to use update.packages() today. All went well for most packages, with the exception of KernSmooth and cluster. In both cases, libraries were not found although I think they are present. Here's what happened: ---------------------------------- >

Hello, has anybody written a function to plot density ellipses (95%, 99% or anything) in a scatterplot? I found nothing in any package, nor in the list archives. There does seem to be a contributed package "ellipse" for S-Plus (on S-Archive), but it does a lot more than what I would need. Still, if anybody ported it to R, I'd be grateful for a link. I'm a bit afraid to try the

Hello all, to obtain a list of all objects in all search paths, I've found the following to work: > biglist <- sapply(1:length(search()), objects) This more obvious one, however, does not work: > biglist <- sapply(search(), objects) Error in pos.to.env(pos) : invalid argument Still, search() gives [1] ".GlobalEnv" "package:ctest" "Autoloads"

Currently (R-1.4.1 as well as R-devel, according to http://stat.ethz.ch/R-alpha/R-devel/library/base/html/par.html), the html version of help(par) shows [...] lab A numerical vector of the form c(x, y, len) which modifies the way that axes are annotated. The values of x and y give the (approximate) number of tickmarks on the x and y axes and len specifies the label size. The default

Hello, does anyone know of a quick way to create a data frame "like" another, but with more rows? What I'd like to do is this: if mydata is a data.frame like a b c 1 TRUE yes 2 FALSE no 3 TRUE yes I'd like to get mydata2 with the same column names and column types, but without the values and with more rows. All I could think of was to manually do

Hello, first, I'd like to congratulate the core team to the new R version 1.1. I think it's a great update, with glimpses into an even greater future (tcltk!). While playing around with the new functions (on Win 95), I found the following: As the documentation states, when I generate a plot and save it with recordPlot, I can regenerate it by printing the variable: > plot(1:10) >

Hello, I'd like to propose an extension to the function summary.aov. In Splus (2000, I don't know about other versions), summary.aov allows a parameter ssType to be set to 1 or 3 (defaults to 1) to choose the type of Sums of Squares. I know I can get Type III SS in R with drop1(model), but including the functionality into summary.aov would, in my opinion, - yield a more usable table

Hello, after thorough searching of the R help files as well as S+-help, I'm coming to the list: Is there a possibility to compute partial correlation coefficients between multiple variables (correlation between two paired samples with the "effects of all other variables partialled out")? All I seem to find are the standard Pearson correlation coefficients (with cor()) and no clue

I think this is pretty certainly a bug, so I'm cc'ing this to r-bugs. -p Kaspar Pflugshaupt <pflugshaupt@geobot.umnw.ethz.ch> writes: > Hello, > > first, I'd like to congratulate the core team to the new R version 1.1. I > think it's a great update, with glimpses into an even greater future > (tcltk!). > > While playing around with the new functions

Hello, I've a question concerning the behaviour of the "scale" function in the base package. I'm using R 1.1.1 on Windows 95. If I take a matrix with NA values, such as > tm <- matrix(c(2,1,0,1,0,NA,NA,NA,0), nrow=3) > tm [,1] [,2] [,3] [1,] 2 1 NA [2,] 1 0 NA [3,] 0 NA 0 and scale it, the columns containing NAs come out all NA: >

Hello, to save searching time in the S-news archive, here is the simple solution to merge data frames vertically (cols must be equivalent, of course). The frames must be components of a list, such as produced by framelist<-split(bigframe,factor). bigframe2<-do.call("rbind",framelist) # posted to S-news by Bill Venables, found in summary message

On Thu, Jun 22, 2000 at 05:01:32PM +0200, p.dalgaard@biostat.ku.dk wrote: > I think this is pretty certainly a bug, so I'm cc'ing this to r-bugs. > > -p > > Kaspar Pflugshaupt <pflugshaupt@geobot.umnw.ethz.ch> writes: > > As the documentation states, when I generate a plot and save it with > > recordPlot, I can regenerate it by printing the variable:

On Thu, Jun 22, 2000 at 05:01:32PM +0200, p.dalgaard@biostat.ku.dk wrote: > I think this is pretty certainly a bug, so I'm cc'ing this to r-bugs. > > -p > > Kaspar Pflugshaupt <pflugshaupt@geobot.umnw.ethz.ch> writes: > > As the documentation states, when I generate a plot and save it with > > recordPlot, I can regenerate it by printing the variable:

This is not a bug. There is no way one can scale the plot axes equally when no indication has been given of the scaling expected for either! It has always seemd to be that plot(x=1, y=1) shoul dnot work: it has not supplied enough information! On Thu, 8 Nov 2001 pflugshaupt@geobot.umnw.ethz.ch wrote: > I found the following in eqscplot, library MASS: > > > When given just one

Hello, I've fitted a parametric survival model by > survreg(Surv(Week, Cens) ~ C(Treatment, srmod.contr), > data = poll.surv.wo3) where srmod.contr is the following matrix of contrasts: prep auto poll self home [1,] 1 1 1.0000000 0.0 0 [2,] -1 0 0.0000000 0.0 0 [3,] 0 -1 0.0000000 0.0 0 [4,] 0 0 -0.3333333 1.0 0 [5,] 0 0

I found the following in eqscplot, library MASS: When given just one point, it fails: > eqscplot(x=1, y=1) Error in plot.window(xlim, ylim, log, asp, ...) : need finite xlim values After inserting browser() just before the last line in eqscplot() (in which plot() gets called), I found the following: > eqscplot(x=1, y=1) Called from: eqscplot(x = 1, y = 1) Browse[1]> xlim [1] NaN

(message from 22.2.2000 13:04 Uhr): > > > Why don't you inverse the modelling instead: > > t.m.i <- lm((x~y) > Jan, thanks for the tip, but it's not just the same. The coefficients come out differently, since the squared y residuals are minimized. Orthogonal regression would be symmetric, but least squares is not, I'm afraid. And, what's more, I have to

Hello, after some searching in the mailing list archives, R-Help and S-Plus-Help, I dare asking the question here: How can I do inverse prediction from a lm model with R? What I want to achieve is this: predict term values for given new response values. If I've got a model t.m<-lm(y?x) I would type something like inverse.predict(t.m, newdata=data.frame(y=1:10)) which would give me new

Hello, after I've read a few answers from the list, I realised that I stated my problem incorrectly: my x values are not _fixed_, as I wrote (I did not set them). They just have no errors to them, but, apart from that, are random. I think I shall be reading up on calibration next. Many thanks for the references! Kaspar -- Kaspar Pflugshaupt Geobotanisches Institut Zuerichbergstr. 38

Hello all, here's a collection of answers I got on my question concerning partial correlation coefficients: Some people gave a simple formula for the three-variable-case, as did Dave Lucy: pcor <- function(v1, v2, v3) { c12 <- cor(v1, v2) c23 <- cor(v2, v3) c13 <- cor(v1, v3) partial <- (c12-(c13*c23))/(sqrt(1-(c13^2)) * sqrt(1-(c23^2)))