similar to: Re: Candid comment

Peter Dalgaard writes: > Bill.Venables at cmis.csiro.au writes: > ........ > > [WNV] Now there's an insight! In fact I think that once you get used to > > the style you get to appreciate it. The commercial world substitutes > > politeness for candour. True candour can be disconcerting but it does get > > the message across much quicker. > Also, this

Perhaps I should have said: "... more than failure to read the manual..." John Maindonald ----------------------------------------------------------------------- Michael Nielsen wrote <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

Fisher is not the only person that it may be necessary to read 4 or 5 times. The same may be the case for side comments that Bill Venables is wont to make. Now to the parallel universe that I have in mind. I wonder whether the time is opportune for a list that focuses on "Statistical Methodology for R Users". The difference from other statistical methodology lists is that it will be

I've changed the heading because this really is another thread. I think it inevitable that there will, in the course of time, be other lists that are devoted, in some shape or form, to the concerns of practitioners (at all levels) who are using R. One development I'd not like to see is fracture along application area lines, allowing those who are comfortable in coteries whose

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 :

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) :

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

I am looking for information on experimentation with the use of R in the teaching of statistics and science in schools. Any leads would be very welcome. I am certain that there is such experimentation. I've made this inquiry on r-sig-teaching, with no response. John. John Maindonald email: john.maindonald at anu.edu.au phone : +61 2 (6125)3473 fax : +61 2(6125)5549 Centre

# 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 <-

In Section 1.4.2 of "Writing R Extensions" %\VignetteEngine{knitr::knitr} should be %\VignetteEngine{knitr::knit} > sessionInfo() R version 3.0.2 (2013-09-25) Platform: x86_64-apple-darwin10.8.0 (64-bit) Is this sort of thing best reported here, or is a huge report in order? John Maindonald email: john.maindonald at anu.edu.au phone : +61 2 (6125)3473 fax

<<< Thus factor analysis is in essence a model for the correlation matrix of x, ? = ?'? + ? >>> This should surely be ? = ??' + ? Also line 3 under ?Details? says <<< for a p?element row-vector x, ? >>> x is here surely a column vector, albeit the transpose of a row vector from the data matrix. cf page 322 of ?Modern Applied Statistics with S?, 4th

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

Finding and not unnecessarily duplicating existing functionality is important also from a user perspective. Negative binomial regression provides a somewhat extreme example of existing overlap between packages, with the scope that this creates for confusing users, especially as the notation is not consistent between these different implementations. In addition to MASS::glm.nb(), note

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

I'd use mcmcsamp() to examine the posterior distribution, under a relatively uninformative prior, of of the parameter estimates. For estimates that are based on four or five or more "degrees of freedom", I'd surmise that the prior will not matter too much. With estimates where the number of "degrees of freedom" is one or two or three, the posterior distribution may vary

The following is 'semicolon.Rnw' > \SweaveOpts{engine=R, keep.source=TRUE} > > <<xycig-A, eval=f, echo=f>>= > library(SMIR); data(bronchit); library(KernSmooth) > @ % > > Code for panel A is > <<code-xycig-A, eval=f, echo=t>>= > <<xycig-A>> > @ % Sweave("semicolon") yields the following 'semicolon.tex'

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,

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