similar to: Is r-announce alive?

formatC() is great for formatting numbers! But it would be even better if it could optionally insert commas (or semicolons), e.g. R> formatC(1234567.89, digits=2, format="f", commas=T) [1] "1,234,567.89" Here's a snippet of code that does that, which could more or less just be inserted into at the end of formatC if any R-core guru were so inclined. "r"

I have a Date x Stock (223 x 520) matrix of "trading volume". I can calculate a 5-day (past) average in about 1 second using: R> apply(vol, 1, filter, filter=c(0, rep(1/5,5)), sides=1) I would like to do the same with a 5-day median, e.g.: R> mymed <- function(x, n=5) { R> r <- rep(NA, length(x)) R> for (i in (n+1):length(x)) r[i] <- median(x[i-(1:n)]) R>

In R-1.5.0pre (2002-04-08) on Solaris 2.6, the window that X11() creates has a title like: R Graphics: Device 2 (ACTIVE) o iyeP )( y except the funny characters at the end have umlauts and other accents (i.e. extended ASCII characters), and they may be different each time X11() is invoked. There is no loss of functionality; it just looks a little ugly. I saw this behavior in R-1.3.?, it

Hi, all! My project today is to write a speedy colSums(), which is a function available in S-Plus to add the columns of a matrix. Here are 4 ways to do it, with the time it took (elapsed, best of 3 trials) in both R and S-Plus: m <- matrix(1, 400, 40000) x1 <- apply(m, 2, sum) ## R=16.55 S=52.39 x2 <- as.vector(rep(1,nrow(m)) %*% m) ## R= 2.39 S= 8.52 x3 <-

Under R-1.5.0 on Solaris 2.6: R> prettyNum(123456789, big.mark=",") [1] ",123,456,789" and that bad behavior (leading comma) spills into formatC as well: R> formatC(123456789, digits=0, format="f", big.mark=",") [1] ",123,456,789" Looks to me like a bug in src/library/base/R/format.R, in function prettyNum: B.[i.big] <-

I've seen references to "polymars", an R implementation of Friedman's MARS algorithm. Can anyone tell me where I might be able to find this (doesn't seem to be in the contributed packages. Thanks, David -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send

Mark Leeds <mleeds at mlp.com> wrote (to S-News): > does anyone know the R equivalent of the SPlus rowVars function ? Andy Liaw <andy_liaw at merck.com> replied: > More seriously, I seem to recall David Brahms at one time had created an R > package with these dimensional summary statistics, using C code. (And I > pointed him to the `two-pass' algorithm for variance.)

Hi, all, I've been converting code from S-Plus ("S" for short) to R for a few weeks. Here are some differences I've found, aside from the big well-known ones (scoping, models, data storage) and the contents of Kurt Hornik's FAQ section 3.3.3. Let me start with the ones that seem like serious bugs or deficiencies: 1) LETTERS[c(NA,2)] in S is

Hi, all, I've been converting code from S-Plus ("S" for short) to R for a few weeks. Here are some differences I've found, aside from the big well-known ones (scoping, models, data storage) and the contents of Kurt Hornik's FAQ section 3.3.3. Let me start with the ones that seem like serious bugs or deficiencies: 1) LETTERS[c(NA,2)] in S is

For your consideration: > z [,1] [,2] [1,] 1 NA [2,] 2 NA [3,] 3 NA > colSums(z) [1] 6 NA Correct, according to the documentation > colSums(z,na.rm=T) [1] 6 0 Surprising to me, but, as documented, correctly consistent with apply() and >sum(NULL) [1] 0 The documentation for sum() explicitly notes that the sum of an empty set is 0 by definition, so that users

I've uploaded a package colSums_1.0.tar.gz to CRAN /src/contrib/Devel. It contains functions colSums, colMeans, colVars, colStdevs, rowSums, rowMeans, rowVars, and rowStdevs. These do simple, fast arithmetic on columns/rows of a matrix, or more generally across dimensions of an array, e.g. colSums(m) = apply(m, 2, sum) but faster. They should be compatible with the corresponding S-Plus

Full_Name: Doug Grove Version: 1.7.0 OS: Linux Submission from: (NULL) (209.31.211.56) Hi, Minor mistake in the documentation on the colSums page. In the ARGUMENTS section it states for 'dims' that: For `col*', the sum or mean is over dimensions `dims+1, ...'; for `row*' it is over dimensions `1:dims'. These two are reversed. Thanks, Doug Grove

Hello all - I've just recently been exploring R for the first time. After noticing a few things that have changed from S to R, I started looking for an R-S compatibility table but didn't find it. Is such a table out there ? Where ? Thanks much, Purvis Bedenbaugh purvis at mbi.ufl.edu Examples: 'stdev' is now 'sd' - is it exactly the same computation ? couldn't find

Hello all, This might have been fixed in later versions (I am using R1.7.0), r-help archive contains messages reporting similar problems but no reports of codes fixes. I have encountered a couple of problems using the silhouette function. one occurs when the clustering contains clusters composed of 1 element (Martin Maechler posted code few months ago that fixes a similar problem that occurs

Hi R users, I am still a relatively new R user migrated from S+. I wonder in R how do you handle one difference between R and S+. S+ saves objects as different files in .Data directory while R saves all objects in a big file .RData. In S+, I can start two S+ sessions from the same directory and work simultaneously as long as new objects in the two sessions are not in the same names. This is

A new package "g.data" is available on CRAN, to create and maintain databases that work more like the S-Plus model. Here's the official Description for g.data (v1.2): Create and maintain delayed-data packages (DDP's). Data stored in a DDP are available on demand, but do not take up memory until requested. You attach a DDP with g.data.attach(), then read from it and assign

A new package "g.data" is available on CRAN, to create and maintain databases that work more like the S-Plus model. Here's the official Description for g.data (v1.2): Create and maintain delayed-data packages (DDP's). Data stored in a DDP are available on demand, but do not take up memory until requested. You attach a DDP with g.data.attach(), then read from it and assign

Hi All: I am clustering 500 genes using hclust of R. Visualizing cluster membership becomes difficult with so many genes in each cluster...Is there a way of printing the dendrogram in multiple pages so that I can clearly see what is in each cluster? Thanks in advance. Karthi.

As many of you have probably realized, the spam filtering at @stat.math.ethz.ch has been dead for since yesterday (09-25) ~16:50 till today ~08:30. The sudden death may have been caused by unrelated installation of some perl modules (spamassassin *is* running on perl) by our IT staff. We are very sorry for this event. On the bright side: You have been able to get a glimpse of what you are

Has anyone ported the Bagplot function by Rousseeuw, Ruts, and Tukey from S to R? The S function comprises a script and a FORTRAN function. I assume porting is relatively uncomplicated, but since I have not done any porting before I would not want to invest the effort if a port is readily available.