similar to: Error in plot.aov() (PR#356) (fwd)

# Your mailer is set to "none" (default on Windows), # hence we cannot send the bug report directly from R. # Please copy the bug report (after finishing it) to # your favorite email program and send it to # # r-bugs@biostat.ku.dk # ###################################################### The error occurs following the third Hit <Return> below: > y_rnorm(40) >

I propose the following enhancements and changes to plot.lm(), the most important of which is the addition of a Residuals vs Leverage plot. (1) A residual versus leverage plot has been added, available by specifying which = 5, and not included as one of the default plots. Contours of Cook's distance are included, by default at values of 0.5 and 1.0. The labeled points, if any, are those

Dear all, I noticed the following behaviour of plot.lm: > fm1 <- lm(time~dist, data=hills, weights=c(0,0,rep(1,33))) > par(mfrow=c(2,2)) > plot(fm1) Warning messages: 1: longer object length is not a multiple of shorter object length in: res/(sd * (1 - hat)) 2: longer object length is not a multiple of shorter object length in: (res/(sd * (1 - hat)))^2 * hat which seems to be

I have been struggling trying to write some code to produce all combinations subject to some restrictions. I thought someone might have some bright ideas. I have 11 values which fall into 5 groups. I want all combinations of 2,3, and 4 values where each value must be from a different group. The numbers in the groups are different. Here is a definition of the groups: groups <- list(gp1 =

I am having trouble plotting one of my graphs (think graph theory graph with edges and vertices, not scatterplots or histograms). For some pairs of vertices, I want multiple edges to be visible in my graph. As an example of this, in my script below, I want two edges to be visible from vertex 1 and vertex 9 (among some others) yet when I plot it, only one edge is visible.

Full_Name: Carsten Dormann Version: 1.4.0 OS: Windows 2000 Submission from: (NULL) (192.171.129.9) Hello, using the function xyplot I repeatedly had R crashing. One example is from the book of Mick Crawley (Stat. Computing in Splus), where the commandline reads: xyplot(Weight~Age|Genotype, pch=16) I also had the same phenomenon with my own data and commands even simpler. I reinstalled

Hi I am trying to do a logistic regression on a small data file yet when i get up to plotting the first set of graphs instead of 4 I only get one graph, and some error messages. Yet it still looks like the program is doing something due to the "blue wheel" of the mouse. Below is the script copied from R and where I get up to before the message occurs. The data set is based on how

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OK, I see now that I was supposed to twig that the reference was to putting the ?.Rnw' files back into the vignettes directory from the inst/doc directory where they?d been placed in the course of creating the tar.gz file. I am still trying to work out what I need to put into ?.Rinstignore? so that ?.install_extras? is not installed. John Maindonald email: john.maindonald at

Sorry. This, and the description in the ?Writing R Extensions? manual, leaves me completely mystified. Is it that I have to remove the PDFs that are created when I run ?R CMD build?, and somehow ensure that they are rebuilt when the package is installed? Do I need a Makefile? John Maindonald email: john.maindonald at anu.edu.au<mailto:john.maindonald at anu.edu.au> phone :

From a quick look at the paper in the SAS proceedings, the simulations seem limited to nested designs. The major problems are with repeated measures designs where the error structure is not compound symmetric, which lme4 does not at present handle (unless I have missed something). Such imbalance as was investigated was not a serious issue, at least for the Kenward and Roger degree of freedom

You've omitted a comma. races2000 is a data frame, which for purposes of extracting rows behaves like a 2-dimenional object. The following works fine: hills2000 <- races2000[races2000$type == 'hill', ] Additionally, you might like to ponder > type <- races2000[names(races2000)=="type"] > type[1:4] Error in "[.data.frame"(type, 1:4) :

<soap-box> While I agree with John about abuse of methodology, I can't subscribe to the "failure to read the manual" proposition. I don't mean to lecture, but it would seem to me that people who, like me, will probably gain far more from this list than we will be able to contribute (at least in the near term) owe it to those who will likely contribute far more than they

It really is unclear what is claimed to be a bug here. But see https://stat.ethz.ch/pipermail/r-devel/2007-May/045592.html for why the bug is not in R: your old and new data do not match. Your fit is to a category. [The problem with the web interface to R-bugs was reported last week: it is being worked on.] On Mon, 30 Apr 2007, r.darnell at uq.edu.au wrote: > This is a multi-part

I have posted, at http://wwwmaths.anu.edu.au/~john/r/newsets/ image (.rda) files, and first stabs at .Rd files for various data on deaths in London from 1629 to 1939. (There are of course gaps.) The sources (Guy 1882 & Stocks 1942) are documented in the .Rd files: (1) poxetc: measles, smallpox & total deaths: 1629-1881 [I have deliberately left several inconsistencies that were in

In the following titletxt <- substitute(paste(tx, tilde(y) == sqrt(y)), list(tx="Replace y by ")) I'd like to be able to replace e.g. sqrt(y) by a symbol or symbolic expression that has the effect of inserting sqrt(y) into the place that it occupies. This would allow me to put an arbitrary expression into that position. [One can use text() or mtext() etc. to place titletxt

# r-bugs@r-project.org The problem occurs when the model matrix has a single column. > elastic <- data.frame(stretch=c(46,54,48,50,44,42,52), distance=c(183,217,189,208,178,150,249)) > elastic.lm <- lm(distance ~ -1 + stretch, data=elastic) > predict(elastic.lm,se=T) Error in XRinv^2 %*% rep(res.var, p) : non-conformable arguments The fix is to replace XRinv <-

The message for aov1 was "Estimated effects <may> be unbalanced". The effects are not unbalanced. The design is 'orthogonal'. The problem is that there are not enough degrees of freedom to estimate all those error terms. If you change the model to: aov1 <- aov(RT~fact1*fact2*fact3+Error(sub/(fact1+fact2+fact3)),data=myData) or to aov2 <-

I''d like to make the following changes (differences are from R1.0.1): boxplot.default() 1c1 < function (x, ..., range = 1.5, width = NULL, varwidth = FALSE, --- > function (x, ..., range = 1.5, width = NULL, varwidth = FALSE, boxwex=0.8, 37c37,38 < bxp(groups, width, varwidth = varwidth, notch = notch, --- > bxp(groups, width, varwidth = varwidth,

Hi Ross - I believe I was wrong in thinking that passing via the ... list to stripchart() was ever allowed. Here are patches: Add ... to the argument list Add, at the beginning of the function: pars <- list(...) There are two calls to axis(). Modify these to: axis(1, at = at, labels = names(groups), las=pars$las) axis(2, at = at, labels = names(groups), las=pars$las) Also