similar to: plotting sorted factors

With current dragonegg svn, the Polyhedron 2005 benchmarks all now pass when using the compiler plugin under FSF gcc 4.6.1 on x86_64-apple-darwin11. The differences between the runtime and compile times when using the same plugin under FSF gcc 4.5.4svn are small. Once new vector_select feature is available in llvm and -fplugin-arg-dragonegg-enable-gcc-optzns supports -ftree-vectorizer we might see

Hello R help-ers, I have a basic question, but I have been playing with it for a while and haven't quite gotten a hang of how to get it working. I want to perform multiple one-way ANOVAs on subsets of data and am not sure how to do it in an automated way. I am thinking of doing something similar to 'aggregate' but I would like to collect all of the ANOVA results in a way in which I

Hi [macOSX 10.4.6; R-2.3.0] I have encountered a difference in behaviour between R-2.2.1 and R-2.3.0 when performing a linear model. Transcript follows for R-2.3.0 (R-2.2.1 worked as expected). How to make R-2.3.0 perform as R-2.2.1 did? > dput(x) c(29.13, 29.88, 30.09, 29.99, 29.74, 29.64, 29.65, 29.7, 30.04, 29.89, 29.96, 29.65, 28.76, 28.41, 28.38, 29.55, 29.76, 29.75, 29.84,

Does something like this get you close: x <- list() keys <- LETTERS[1:6] # create for (i in keys){ x[[i]] <- data.frame(a=1:5, b=1:5, c=1:5) } # output output <- file('tempxx.txt', 'w') for (i in keys){ write.table(i, row.names=FALSE, col.names=FALSE, file=output, quote=FALSE) write.table(x[[i]], file=output, quote=FALSE) } close(output) On Wed, Jul 2,

Hi, I am trying to plot the Case-Shiller index found at: http://www2.standardandpoors.com/spf/pdf/index/CSHomePrice_History_022445.xls The way I'm importing it into R is as follows: library(gdata) W <- read.xls("http://www2.standardandpoors.com/spf/pdf/index/CSHomePrice_History_022445.xls ", header=TRUE) attach(W) To give you and idea of what the data looks like: >

Dears members of R list, It would like that a more experienced statician in R helped me to complete the analysis to follow: r = gl(3, 8, label = c('r1', 'r2', 'r3')) e = rep(gl(2, 4, label = c('e1', 'e2')), 3) y = c(26.2, 26.0, 25.0, 25.4, 24.8, 24.6, 26.7, 25.2, 25.7, 26.3, 25.1, 26.4, 19.6, 21.1, 19.0, 18.6, 22.8, 19.4, 18.8, 19.2, 19.8, 21.4,

Dears members of R list, It would like that a more experienced statician in R helped me to complete the analysis to follow: r = gl(3, 8, label = c('r1', 'r2', 'r3')) e = rep(gl(2, 4, label = c('e1', 'e2')), 3) y = c(26.2, 26.0, 25.0, 25.4, 24.8, 24.6, 26.7, 25.2, 25.7, 26.3, 25.1, 26.4, 19.6, 21.1, 19.0, 18.6, 22.8, 19.4, 18.8, 19.2, 19.8, 21.4,

Hi, I'm trying to use the R Survival analysis on a windows 7 system. The input data format is described at the end of this mail. 1/ I tried to perform a survival analysis including stratified variables using the following formula. cox.xtab_miR=coxph(Surv(time, status) ~ miR + strata(sex,nbligne, age), data=matrix) and obtain the following error message Warning message: In fitter(X, Y,

Hi guys,   I have two data sets of prices: endprice0, endprice1   I use the Wilcox test:   wilcox.test(endprice0, endprice1, paired = TRUE, alternative = "two.sided",  conf.int = T, conf.level = 0.9)   The result is with V = 1819, p-value = 0.8812.   Then I calculated the z-value of the test: z-value = -2.661263. The corresponding p-value is: p-value = 0.003892, which is different from

https://bugs.freedesktop.org/show_bug.cgi?id=100423 Bug ID: 100423 Summary: MMIO read of 00000000 FAULT at 022554 [ IBUS ] Product: xorg Version: unspecified Hardware: Other OS: All Status: NEW Severity: normal Priority: medium Component: Driver/nouveau Assignee: nouveau at

On Sat, 2011-10-29 at 15:16 -0500, Hal Finkel wrote: > On Sat, 2011-10-29 at 14:02 -0500, Hal Finkel wrote: > > On Sat, 2011-10-29 at 12:30 -0500, Hal Finkel wrote: > > > Ralf, et al., > > > > > > Attached is the latest version of my autovectorization patch. llvmdev > > > has been CC'd (as had been suggested to me); this e-mail contains > >

I have been trying to do a nls model and gives me the error of a nonnumeric argument table(file="c:/tt2.txt",header=T) > fit.model <- nls(TT~60*(1+alpha*(v/c)^beta),data=tt2, start=list(alpha=1, beta=3, v=1000)) Error in v/c : non-numeric argument to binary operator > is.numeric(tt2) [1] FALSE > is.character(tt2) [1] FALSE > as.numeric(tt2) Error: (list)