similar to: eqscplot() in library MASS: fails when given only one point (PR#1164)

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

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 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, 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, 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, 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: >

(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)))

Hello, this is probably more a statistical question than an R-specific problem, but I'll risk it. I've fitted a Cox Proportional hazard model with one factor Treatment (seven levels) as a predictor variable. The general Null hypothesis (all groups show the same survival behaviour) is clearly rejected. Now, is there any (statistically sensible) way of doing pairwise comparisons and/or

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

I had run into problems when compiling some contributed packages to an installation of R 1.40 by fink on MacOS X. Namely, packages KernSmooth (2.22-7) and cluster (1.4-0) would not find required libraries, though those were present on the system. Jeff Whitaker, the maintainer of the R fink packages, kindly sent me this: > Kaspar: It's not looking in /sw/lib, where the libs are (the

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

[Env: R 2.12.2, Win XP] I'm creating figures using MASS::eqcsplot to provide equal scaling of the axes. My figures work OK when I plot to the screen, but when I try to do the same plot as a postscript file, I get an unexplicable error, > figframe() Error in if (yuin > xuin * ratio) yuin <- xuin * ratio else xuin <- yuin/ratio : missing value where TRUE/FALSE needed >

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

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, 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

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: