similar to: Base and lattice graphics on the same graphics page

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

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) :

This message is aimed at anyone who may be using exercises from my book with John Braun for teaching purposes. I am using this channel of communication in the absence of any other obvious effective channel. I ask the forbearance of list members. Our intention is to post solutions to selected exercises (the more challenging exercises) on the web, via a link from

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

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

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 :

With lme4, use of mcmcsamp can be insightful. (Douglas Bates drew my attention to this function in a private exchange of emails.) The distributions of random effects are simulated on a log scale, where the distributions are much closer to symmetry than on the scale of the random effects themselves. As far as I can see, this is a straightforward use of MCMC to estimate model parameters; it is not

expression() accepts multiple expressions as arguments, thus: plot(1:2, 1:2) legend("topleft", expression(y == a * x^b, "where "* paste(y=="wood; ", x=="dbh"))) Is there a way to do this when values are to be substituted for a and b? i.e., the first element of the legend argument to legend() becomes,

<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

Typing in statements from the command line transfers to the computer a macro that was perhaps in the user's head. Putting together small sequences of carefully thought out code, in which key components have been carefully thought out and tested, has to be, for most of us, better than trying to make it all up on the run. An exception is necessary for those unusual people who who (akin to the

The following failed to make it to r-help when Murray Jorgensen sent his message a little time ago. [It seems to have been an issue of the machine from which my message originated.] Typing in statements from the command line transfers to the computer a macro that was perhaps in the user's head. Putting together small sequences of carefully thought out code, in which key components have been

Under help(matrix) it is written: 'is.matrix' tests if its argument is a (strict) matrix. It is generic: you can write methods to handle specific classes of objects, see InternalMethods. Further down, under "Details", the meaning of "strict" is explained more explicitly: 'is.matrix' returns 'TRUE' if 'x' is a matrix

I'd like to make the following change to termplot(): Add panel=points as an extra parameter. Replace if (partial.resid) points(xx, pres[, i], cex = cex, pch = pch, col = col.res, ...) by if (partial.resid) panel(xx, pres[, i], cex = cex, pch = pch, col = col.res, ...) Also, I think, add col.smooth, span and iter as named parameters; see below.

The following works fine with the x11 device, though it may well be that an initial plot is overwritten. With a pdf or postscript device, I get two plots, the first of which still has the red border from having the focus, while the second is the plot that I want. library(lattice); library(grid) plt <- xyplot(uptake ~ conc, groups=Plant, data=CO2) print(plt)

R-help Digest Friday, December 3 1999 Volume 01 : Number 034 In this issue: [R] model.tables Re: [R] Installing R on Slackware Linux Re: [R] Installing R on Slackware Linux [R] nlmin Re: [R] nlmin Re: [R] nlmin Re: Summary: [R] Wanted: online Introduction to R [R] Applying a function of several variables to data Re: [R] R and XML -- a near perfect

There are answers that could and should be applied in specific situations. At least in academia and in substantial research teams, statisticians ought to have a prominent part in many of the research teams. Senior statisticians should have a prominent role in deciding the teams to which this applies. why should it be ok to do combine high levels of chemical expertise with truly appalling

I am puzzled by the warning message in the output below. It appears whether or not I fit the seasonal term (but the precise point of doing this was to fit what is effectively a second seasonal term). Is there some deep reason why AR parameters ("Warning message: some AR parameters were fixed: ...") should somehow intrude into the fitting of a model that has only MA terms? >

Is there any way, after use of print.trellis(), to obtain the co-ordinates of the plot region, e.g., in what are then the native co-ordinates? e.g. library(DAAG) library(lattice); library(grid) data(cuckoos) pushViewport(viewport(layout=grid.layout(2, 1))) pushViewport(viewport(layout.pos.row=1)) cuckoos.strip <- stripplot(species ~ length, data=cuckoos) print(cuckoos.strip,

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 <-

In co-operation with Markus Hegland and myself, Zhongwen Ding has written a package, based partly on Markus Hegland's code, that provides a parallel processing interface to a remote multi-processsor system. Pyro (Python Remote Objects) and R must both be installed, both on the client machine and on the remote server. The system uses rsync, with an ssh protocol, to handle file transfer. Once