similar to: debugging

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

## the following is a dream: add some sugar syntax to allow for contracts with teeth (in and out checking) > is.positive <- function(x) (all(x>0)) > exponentiate <- function( x ::is.data.frame , exponent ::is.numeric is.positive) :: is.vector is.numeric { x$base :: is.positive ## error also if base does not exist in x; may need some special IQ x$base^exponent }

I am using a variant of stopifnot a lot. can I suggest that base R extends its functionality? I know how to do this for myself. this is a suggestion for beginners and students. I don't think it would break anything. first, I think it would be more useful if it had an optional character string, so users could write stopifnot( is.matrix(m), "m is not a matrix" ) this would

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

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 Users--- [Because I struggled with this for a while, I decided to post it into r-help for the benefit of others, where google search will pick it up. thanks to everyone who made these facilities available.] The task is to use your own opentype otf fonts in an R-created pdf file using the pdf device (not with the [excellent] CairoPDF device, if only because it does not have colorspace

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

quick programming question. I am not making enough errors in my programs, so I want to trigger a few more. ;-) [1] undefined variable behavior: > d=data.frame( x=rnorm(1:10), y=rnorm(1:10)) > z Error: object 'z' not found > d$z NULL is this consistent? I thought that z is the same as .GlobalEnv$z, but apparently it is not. something here is smart enough to trigger an error.

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 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);

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

dear R graphics experts---if anyone is running the combination of R 2.7.0 and ghostscript (2.62), could you please run the following and let me know if you get the same strange symbol size that I do, or if there is something weird on my system? regards, /ivo pdf(file = "testhere.PDF", version="1.4", pointsize=14); plot(0, xlim=c(0,26), ylim=c(-1,4.5), type="n"

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

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: I am trying (finally) to build a function that might be useful to others. In particular, I want to create a summary.lme (extended lm) method that [a] adds normalized coefficients and [b] white heteroskedasticity adjusted se's and T's. I believe I already know how to do the programming to do these two, at least in simple unweighted cases. Now my challenges are just [1]

Dear R Wizards---is it possible to get R to show its current call stack (sys.calls()) upon an error abort? I don't use ESS for execution, and it is often not obvious how to locate how I triggered an error in an R internal function. Seeing the call stack would make this easier. (right now, I sprinkle "cat" statements everywhere, just to locate the line where the error appears.) Of

curiosity---given that vector operations are so much faster than scalar operations, would it make sense to make uniroot vectorized? if I read the uniroot docs correctly, uniroot() calls an external C routine which seems to be a scalar function. that must be slow. I am thinking a vectorized version would be useful for an example such as of <- function(x,a) ( log(x)+x+a ) uniroot( of, c(

Dear R wizards: I am playing (and struggling) with the example in the constrOptim function. simple example. let's say I want to constrain my variables to be within -1 and 1. I believe I want a whole lot of constraints where ci is -1 and ui is either -1 or 1. That is, I have 2*N constraints. Should the following work? N=10 x= rep(1:N) ci= rep(-1, 2*N) ui= c(rep(1, N), rep(-1, N))

dear R wizards: I am looking for a binary package distribution of R 2.9.2 for OSX . Looking at http://r.research.att.com/ , there seems to be only a binary for 2.9.0 . is the 2.9.2 version binary package available somewhere? (at this point, would it make sense to elevate the 64-bit version to a "standard recommended" rather than just a "boutique" version?) sincerely, /iaw