similar to: Minimal DESCRIPTION file

I have a daily job that attaches hundreds of pseudo-packages containing data as promise objects (DDP's, ref: g.data package), and plots the results to a multi-page pdf device. Sometimes it fails. Under R-2.2.1 it just gave segfaults. Under R-2.3.1 it gave this error message: *** caught segfault *** address (nil), cause 'memory not mapped' Traceback: 1:

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

I want to put multiple plots on a page using par(mfrow), then a single title at the top. This should work, but doesn't: R> par(oma=c(0,0,4,0), mfrow=c(3,4)) R> for (i in 1:12) {plot(1); title(i)} R> ## text(10,10, ".") R> par(mfrow=c(1,1), oma=c(0,0,1,0)) R> title("Main Title") The main title does not appear. However, uncommenting the third line

I am new on R, so I have a maybe naive question: if I have many large data.frames and I use only one or two per session, what's the best way? If all are stored in the actual .Rdata, the system gets slow. On the other hand, I wouldn't like to make a separate package for the data. Should I save it with save() and then remove it with rm() ? Could I reload it then? Thanks for suggestions

Any doubts about R's big-league status should be put to rest, now that we have a Sudoku Puzzle Solver. Take that, SAS! See package "sudoku" on CRAN. The package could really use a puzzle generator -- contributors are welcome! -- David Brahm (brahm at alum.mit.edu) [[alternative HTML version deleted]] _______________________________________________ R-packages mailing list

Any doubts about R's big-league status should be put to rest, now that we have a Sudoku Puzzle Solver. Take that, SAS! See package "sudoku" on CRAN. The package could really use a puzzle generator -- contributors are welcome! -- David Brahm (brahm at alum.mit.edu) [[alternative HTML version deleted]] _______________________________________________ R-packages mailing list

Version 1.4 of package "g.data" is available on CRAN. This upgrade is necessary for it to work under R-1.8.0, and is fully backward compatible. Description: 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 to it in a

Version 1.4 of package "g.data" is available on CRAN. This upgrade is necessary for it to work under R-1.8.0, and is fully backward compatible. Description: 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 to it in a

as.character.factor contains this line (where cx=levels(x)[x]): if ("NA" %in% levels(x)) cx[is.na(x)] <- "<NA>" Is it possible that this is no longer the desired behavior? These two results don't seem very consistent: > as.character(as.factor(c("AB", "CD", NA))) [1] "AB" "CD" NA > is.na(.Last.value)[3] [1] TRUE

The following code produces 6 plots on a page, but the first is distorted and different from the others: par(mfrow=c(3,2), las=2) for (i in 1:6) { frame() par(mar=c(7, 7, 1, 1)) axis(2); box(); abline(h=seq(0,1,.5), col=2:4) } The first plot's axes are mis-aligned with the plotting area implied by the box. It seems to be a result of calling par(mar) after frame(). Is this expected

Thanks to David Meyer [david.meyer@ci.tuwien.ac.at] and David Brahm [brahm@alum.mit.edu] who suggested: m[ cbind(index.i, index.j) ] <- vals This works fine for the example I gave. Unfortunately, this approach doesn't extend to using the row and column names to make assignments: > m <- matrix("",ncol=3,nrow=3) > dimnames(m) <-

R> x <- 0. + 1:8000 R> y <- outer(-x, x, pmin) Error: cannot allocate vector of size 1000000 Kb Why does R need to allocate a gigabyte to create an 8000 x 8000 matrix? It doesn't have any trouble with outer(-x, x, "+"). Thanks. -- David Brahm (brahm at alum.mit.edu) Version: platform = i686-pc-linux-gnu arch = i686 os = linux-gnu system = i686, linux-gnu status =

After upgrading to R-2.3.1 on Linux Redhat, I was suprised by this: R> x <- c(721.077, 592.291, 372.208, 381.182) R> sum(x) - 2066.758 [1] 4.547474e-13 Now I understand that floating point arithmetic is not precise, but 1) the result is exactly 0 in R-2.2.1 (patched) on the same machine, 2) .Machine$double.eps = 2.2e-16, so the error seems quite large. Also note I get the same

Version 1.6 of the "g.data" package is available on CRAN. The "g.data" package is used to 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 to it in a manner similar to S-Plus, except that you must run g.data.save() to

Version 1.6 of the "g.data" package is available on CRAN. The "g.data" package is used to 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 to it in a manner similar to S-Plus, except that you must run g.data.save() to

I sent a message to <r-announce at stat.math.ethz.ch> last Thursday ("New package: colSums"), and still haven't seen it echoed on r-help or on the web archive (in fact there is no r-announce web archive for 2002). Is something broken? Did I need to use <r-announce at lists.R-project.org> instead? -- -- David Brahm (brahm at alum.mit.edu)

In a clean environment under R-2.1.0 on Linux: > x <- 1:5 > x[3] <<- 9 Error: Object "x" not found Isn't that odd? (Note x <<- 9 works just fine.) Why am I doing this? Because I'm stepping through code that normally lives inside a function, where "<<-" is appropriate. -- David Brahm (brahm at alum.mit.edu)

In R-patched_2003-10-20, subsetted 1-D arrays no longer get converted to vectors. The NEWS file documents this change, as an indirect result of bug report 4110. I just wanted to mention this can break code in some rather obscure ways, such as this toy example: R> x <- sort(tapply(1:8, rep(1:4,2), sum)) # Was vector, now is 1D array R> y <- matrix(1:4, 1,4) #

I'd like to play with ARIMA models of stock prices, but I am a complete novice. Could some kind soul explain the relationship among packages "ts", "tseries", "dse", "dse2", and "fracdiff"? Are they 'competing' products or does one depend on another? Where would be the best place for a novice to begin? Thanks for any advice. PS. I