similar to: stop() vs. error() ?

dear R wizards: an operation I execute often is the deletion of all observations (in a matrix or data set) that have at least one NA. (I now need this operation for kde2d, because its internal quantile call complains; could this be considered a buglet?) usually, my data sets are small enough for speed not to matter, and there I do not care whether my method is pretty inefficient (ok, I

is it possible to throw a stop() that is so hard that it will escape even tryCatch? /iaw ---- Ivo Welch (ivo.welch at gmail.com)

Dear R experts--- after many years, I am planning to give in and write my first R package. I want to combine my collection of collected useful utility routines. as my guide, I am planning to use Friedrich Leisch's "Creating R Packages: A Tutorial" from Sep 2009. Is there a newer or better tutorial? this one is 4 years old. I also plan on one change---given that the

I ran into an interesting oddity of R, if (0) { print(1); } else { print(2); } is a syntax error, while if (0) { print(1); } else { print(2); } or if (0) { print(1); } else { print(2); } is not. I presume it has to do with the duality of the newline functioning as an end of command (;) character, though it still seems a bit odd, and it took me a while to figure out

hi: I searched the last 2 hours for a way to enter a data frame directly in my program. (I know how to read from a file.) that is, I would like to say something like d <- this.is.a.data.frame( c("obs1name", 0.2, 0.3), c("obs2name", 0.4, 1.0), c("obs3name", 0.6, 2.0) ,

dear R experts--- I am experimenting with multicore processing, so far with pretty disappointing results. Here is my simple example: A <- 100000 randvalues <- abs(rnorm(A)) minfn <- function( x, i ) { log(abs(x))+x^3+i/A+randvalues[i] } ?## an arbitrary function ARGV <- commandArgs(trailingOnly=TRUE) if (ARGV[1] == "do-onecore") { ?library(foreach) ?discard <-

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 experts---Is there a multicore equivalent of by(), just like mclapply() is the multicore equivalent of lapply()? if not, is there a fast way to convert a data.table into a list based on a column that lapply and mclapply can consume? advice appreciated...as always. regards, /iaw ---- Ivo Welch (ivo.welch at gmail.com)

every time I read the R release notes for the next release, I see many functions that I had forgotten about and many functions that I never knew existed to begin with. (who knew there were bibtex facilities in R? obviously, everyone except me.) I wonder whether there is a complete list of all R commands (incl the standard packages) somewhere, preferably each with its one-liner AND

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

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

Hi I use gnls to fit non linear models of the form y = alpha * x**beta (alpha and beta being linear functions of a 2nd regressor z i.e. alpha=a1+a2*z and beta=b1+b2*z) with variance function varPower(fitted(.)) which sounds correct for the data set I use. My purpose is to use the fitted models for predictions with other sets of regressors x, z than those used in fitting. I therefore need to

Dear R community, In the excellent nlme package the default diagnostic plot graphs the innermost residuals against innermost fitted values. I recently fit a mixed-effects model in which there was a very clear positive linear trend in this plot. I inferred that this trend occurred because my fixed effect was a two-level factor, and my random effect was a 12-level factor. The negative residuals

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()

dear R experts---is there a function that prints a data frame to a string? cat() cannot handle lists, so I cannot write cat("your data frame is:\n", df, "\n"). regards, /iaw ---- Ivo Welch (ivo.welch@gmail.com) [[alternative HTML version deleted]]

dear R experts---I am trying to replicate a perl feature. I want to be able to embed R commands inside a character string, and have the string be printed with the command executed. my perl equivalent is my $a=10; my $teststring = "the expression, $a+1, is ::$a+1::, but add one more for ::$a+2::\n"; $teststring =~ s/::(.*?)::/$1/gee; print $teststring; of course, R does not use

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 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

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

## 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 }