similar to: finding method file?

dear R wizards: while extolling the virtues of R, one of my young econometrics colleagues told me that he still wants to run ox because [a] his code is written in it (good reason); [b] because ox seems to be faster than R in most benchmarks (huh?). this got me to wonder. language speed can't matter much, so it must be mostly the underlying matrix algebra by now. I presume that nowadays

Hi, I am trying to build R 2.2.1 with Kazushige Goto's BLAS library (libgoto) and encountered a problem: I have two computers with the almost identical hardware (P4 Northwood CPU, i875 chipset, 2GB DDR400 RAM) and identical Linux OS. I have the latest version of libgoto for this CPU installed on both boxes (libgoto_northwood32p-r1.00.so) and I am using gcc compiler flags "-O2

dear R experts---now I have a case where I want to estimate very large regression models with many fixed effects---not just the mean type, but cross-fixed effects---years, months, locations, firms. Many millions of observations, a few thousand variables (most of these variables are interaction fixed effects). could someone please point me to packages, if any, that would help me estimate such

dear debian-R group: I am using the stock ubuntu binary R 3.0.1 for ubuntu raring but on cinnamon mint olivia 15. I read dirk's gcbd paper from a couple of years ago. it suggests that stock blas is pretty bad compared to the four main alternatives. of course, dirk also maintains the binaries for debian/ubuntu R, so he probably knows the answer off hand. I installed libatlas3-base

Dear R wizards: is there a clean way to assign to elements in a list? what I would like to do, in pseudo R+perl notation is f <- function(a,b) list(a+b,a-b) (c,d) <- f(1,2) and have c be assigned 1+2 and d be assigned 1-2. right now, I use the clunky x <- f(1,2) c <- x[[1]] d <- x[[2]] rm(x) which seems awful. is there a nicer syntax? regards, /iaw ---- Ivo Welch

Hi, I'd like to install the optimized libraries on my Thinkpad with an Intel Core Solo chip, which apparently supports the following instruction sets: MMX, SSE, SSE2, SSE3 instruction sets, XD-Bit. In a recent r-help message, the following was said (by Dirk I think): <quote> Yes, on Ubuntu, use 'apt-get install atlas3-base' for basic tuned Atlas, or 'apt-get install

Dear R wizards: I decided to take the advice in the R data import/export manual and want to learn how to work with SQL for large data sets. I am trying SQLite with the DBI and RSQLite database interfaces. Speed is nice. Alas, I am struggling to find a tutorial that is geared for the kind of standard operations that I would want in R. Simple things: * how to determine the number of rows in a

dear R experts---I am using the coef() function to pick off the coefficients from an lm() object. alas, I also need the standard errors and I need them fast. I know I can do a "summary()" on the object and pick them off this way, but this computes other stuff I do not need. Or, I can compute (X' X)^(-1) s^2 myself. Has someone written a fast se() function? incidentally, I think

dear R wizards:? I am wrestling with reshape.? I have a long data set that I want to convert into a wide data set, in which rows are firms and columns are years. > summary(rin) firm fyear sim1 Min. :1004.00 Min. :1964.0 Min. : -1.00000 1st Qu.:1010.00 1st Qu.:1979.0 1st Qu.: -0.14334 Median :1016.00 Median :1986.0 Median : 0.00116 Mean

this is not an important question, but I wonder why lm returns an error, and whether this can be shut off. it would seem to me that returning NA's would make more sense in some cases---after all, the problem is clearly that coefficients cannot be computed. I know that I can trap the lm.fit() error---although I have always found this to be quite inconvenient---and this is easy if I have only

dear R wizards: here is the strange question for the day. It seems to me that nrow() is very slow. Let me explain what I mean: ds= data.frame( NA, x=rnorm(10000) ) ## a sample data set > system.time( { for (i in 1:10000) NA } ) ## doing nothing takes virtually no time user system elapsed 0.000 0.000 0.001 ## this is something that should take time; we need to add 10,000

dear R experts: I have an academic question that borders on asking for consulting help, so I hope I am not too imposing. If I am, please ignore me. My data set has 100MB data set of daily stock returns. I want to compute rolling (recursive?) betas---either bivariate or multivariate---with respect to some other data time series. Many of these regressions are "take away the first

Dear R wizards: This must have an obvious solution, but I am stumped. I can run a linear regression giving a matrix as the independent set of variables, but if I give a data frame (which I would like to give, because it should tell the linear model the names of the variables), R does not like it. An example is: N=20; y= rnorm(N); x.m <- (matrix( nrow=N, ncol=2 )); x.m[,1]=rnorm(N);

Emmanuel, On 30 August 2008 at 00:04, Emmanuel Charpentier wrote: | Dear list, | | Setup : Ubuntu Hardy + updates + backports + security + R repository on | a 3.2 GHz PIV dual-core processor. | | Bitten (again...) by the "I'll optimize my setup" bug, I tried to test | atlas. Following Dirk's advice on a not-so-recent post to R-help, I | tried "apt-get install -s

Dear R wizards---I read Brian Ripley's post from 2004 which said that it was not possible to print to STDERR. Alas, I have more modest needs. I was wondering if it was possible to just send a string to STDERR with cat() while in CMD BATCH mode. Is it not possible to open STDERR in R? (Or does R use STDERR for itself and redirect it into the output stream?) This would be on a standard Unix

As an end-user, I wonder about Revolution R. Is the relationship between Revolution R and the R community at-large a positive one? Do the former contribute to the development efforts of the latter? Is there a competitive aspect? is their forum competitive with r-help? any other thoughts? (most of all, I simply hope that they help some of the many helpful experts on this forum, who have

Dear Statisticians--- This is not even an R question, so please forgive me. I have so much ignorance in this matter that I do not know where to begin. I hope someone can point me to documentation and/or a sample. I want to compute a covariance as quickly as non-humanly possible on an Intel core processor (up to SSE4) under linux. Alas, I have no idea how to engage CPU vectorization. Do I need

dear R experts: has someone written a function that returns the results of by() as a data frame? ??of course, this can work only if the output of the function that is an argument to by() is a numerical vector. presumably, what is now names(byobject) would become a column in the data frame, and the by object's list elements would become columns. it's a little bit like flattening the by()

CentOS Errata and Bugfix Advisory 2012:0402 Upstream details at : https://rhn.redhat.com/errata/RHBA-2012-0402.html The following updated files have been uploaded and are currently syncing to the mirrors: ( sha256sum Filename ) i386: 320a3e16757cf64aeafb019443fac8dca0134c64ad70e1d86d64b492e171fa68 atlas-3.8.4-2.el6.i686.rpm 2946842d8d8545e9fb1bb711be4b68d7b6a88c54127f0c02e9c21976520bb8f7

On two laptops running 32-bit kubuntu, I have found that svd(), invoked within R 2.9.1 as supplied with the current ubuntu package, returns very incorrect results when presented with complex-valued input. One of the laptops is a Dell D620, the other a MacBook Pro. I've also verified the problem on a 32-bit desktop. On these same systems, R compiled from source provides apparently