similar to: In which application areas is R used?

Hi, there: I am looking for a regression modeling (like regression trees) approach for a large-scale industry dataset. Any suggestion on a package from R or from other sources which has a decent accuracy and scalability? Any recommendation from experience is highly appreciated. Thanks, Weiwei -- Weiwei Shi, Ph.D "Did you always know?" "No, I did not. But I believed..."

Can anyone suggest an equivalent, for lattice graphs, of the base graphics argument bty="l"? NB that I am leaving off the box around the strip, with a strip function: stripfun <- function(which.given,which.panel, factor.levels=as.expression(levlist), ...){ panel.text(x=0, y=0.5, lab = as.expression(levlist[which.panel[which.given]]),

Does anyone know any more than is in the following press release about REvolution Computing and their commercialization of R? http://www.intel.com/capital/news/releases/080122.htm "Intel Capital, the global investment arm of Intel Corporation, today announced that it has invested in the Series A financing of REvolution Computing, creator of parallel computing software for computational

Respected Sir/Madam, I have a question regarding calculation of LD50 (Lethal Dose) and IC50 (50% inhibitory concentration) of an antimicrobial experiment. I have used a compound isolated from a plant and observed its effect on the fungus *Fusarium oxysporum* by the food poisoning method. Solutions of the compound at concentrations of 0, 50, 100, 150, 200 and 250µg/ ml were added to

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

help(letters, htmlhelp=TRUE) fails. Under the Mac OSX gui, the message is 'Help for the topic "a" was not found.' Under the version documented below, and under Windows, the message is "No documentation for 'a' in specified packages and libraries:" repeated for all the elements of letters, then followed by "you could try

I'm looking to buy a new desktop which will primarily be used for analyses of large datasets (100s of MB). I've seen postings from several years back re the 'optimal' platform for running R, but nothing more recently. Specifically, I want to know: 1) if I run R under Windows, does having a dual-processor machine help speed things up? And 2) is it still true that R performs

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

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

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'

The inst/doc directory of the DAAG package has 6 files coral551.spot, ... that are around 0.85 MB each. It would be useful to be able to zip then, but that as matters stand interferes with the use of the Sweave file that uses them to demonstrate input of expression array data that is in the "spot" format. They do not automatically get unzipped when required. I have checked that

I apologize if this question is not completely appropriate for this list. I have been using SAS for a while and am now in the process of learning some C and R as a part of my graduate studies. All of the statistical packages I have used generally yield p-values as a default output to standard procedures. This week I have been reading "Testing Precise Hypotheses" by J.O. Berger

I have a file 4lmetc.Rnw, intended for inclusion in a LaTeX document, that starts: \SweaveOpts{engine=R, keep.source=TRUE} \SweaveOpts{eps=FALSE, prefix.string=snArt/4lmetc} The attempt to process the file through Sweave generates the error: > Sweave("4lmetc") Writing to file 4lmetc.tex Processing code chunks ... 1 : keep.source term verbatim Error in file(srcfile$filename, open =

I get the same style of path as Hadley. This is on Windows 7 Home Premium with SP1. I start R by clicking on the R-2.31.0 icon. I'd assumed that it was a change that came with R-2.13.0! (On 32-bit Windows XP, which I have just checked, I do indeed get the 8.3 paths.) > R.home() [1] "C:/Programs/R/R-2.13.0" > sessionInfo() R version 2.13.0 (2011-04-13) Platform:

rug() may add integer axis labels when called with a POSIXlt object as argument. dtimes <- c("09/29/2007 12:54", "09/30/2007 00:14", "10/01/2007 00:14", "10/02/2007 00:14", "10/03/2007 00:14", "10/04/2007 00:14", "10/05/2007 00:14", "10/06/2007 00:14", "10/07/2007

Although the specific behaviour that was reported has been fixed, bugs remain in Sweave's processing of comment lines when keep.source=TRUE This is in some senses a follow-up from earlier bugs. Hence the query -- what is the preferred procedure, to submit a new bug report? (Another option might be to add a comment to the web page for bug 14459.) Is there now a preference to submit via

Dear R community, In the excellent nlme package the default diagnostic plot graphs the innermost residuals against innermost fitted values. I recently fit a mixed-effects model in which there was a very clear positive linear trend in this plot. I inferred that this trend occurred because my fixed effect was a two-level factor, and my random effect was a 12-level factor. The negative residuals

Consider the following analysis of a class experiment done as a Latin Square: > spinner <- gl(4,4,16,label=c("Murray","Angela","Shasha","Stephen")) > order <- gl(4,1,16) > treat <- scan() 1: 1 2 4 3 5: 4 3 1 2 9: 3 4 2 1 13: 2 1 3 4 17: Read 16 items > coin <-

In the following, 'probability=T' is ignored, i.e. the vertical axis is labelled in frequencies. However hist(islands, freq=F) achieves the desired effect. > data(islands) > hist(islands, probability=T) # Vertical axis gives frequencies > hist(islands, freq=F) # Expected result --please do not edit the information below-- Version: platform = i386-pc-mingw32