similar to: 64-bit OSX binary for 2.9.2

Sorry, one more: on OSX, I deleted my old 2.9.2 R.app, and installed the 64 bit version of 2.9.0. I then did an "install.packages("car")" under my new 2.9.0. It seems to have worked, but alas, I still get an error that package 'car' was built under R version 2.9.2 . Where exactly does R under OSX install its packages? (is it a bug that another car is loaded?) PS:

dear wizards: FYI: gentoo is a linux meta distribution, which compiles all packages. Once running, gentoo is stable on most applications. (it has some problems with system tools, such as grub.) the compiler is gcc 3.3.3. I do not expect anyone to track down for me why R fails on the gentoo amd64+gcc3.3.3 system, but I thought that it would be good to put it on the record to save

dear wizards: FYI: gentoo is a linux meta distribution, which compiles all packages. Once running, gentoo is stable on most applications. (it has some problems with system tools, such as grub.) the compiler is gcc 3.3.3. I do not expect anyone to track down for me why R fails on the gentoo amd64+gcc3.3.3 system, but I thought that it would be good to put it on the record to save

dear wizards: my .Rprofile has just one command for testing, loadhistory("~/.Rhistory") but this gives me an error on R startup: Error: couldn't find function "loadhistory" Invoking loadhistory() as the first interactive command works fine; incidentally, I believe loadhistory() in the .Rprofile worked in earlier or other platform R releases, too. Is the .Rprofile

Dear R wizards: under R-2.1.0: eargs <- 3:5; line <- paste(c("echo A B", eargs)); cat("executing from R: '", line, "'\n"); system(line); Oddly, only "A" and "B" are echoed, not the eargs. I had hoped that line would be one string at this point, and for printing this seems to be true. However, unlist(line) still gives me the 4

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

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---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

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))

I am about to write a "cluster-lite" R solution for myself. I wanted to know whether it already exists. If not, I will probably write up how I do this, and I will make the code available. Background: we have various linux and OSX systems, which are networked, but not set up as a cluster. I have no one here to set up a cluster, so I need a "hack" that facilitates parallel

dear R wizards: is it possible to use a postscript font symbol as a plot symbol? in particular, I want to use the four postscript symbols for playing cards (club, heart, spade, diamond) as points. In LaTeX, these four are \Pisymbol{psy}{"A7} \Pisymbol{psy}{"A8} \Pisymbol{psy}{"A9} \Pisymbol{psy}{"A10} and what I would love to do is place them, at say, (x=1,y=1),

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

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 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

I sent this privately to ivo welch yesterday, and he thinks it might be useful to someone else as well. Since I'm on a Mac the screen device is quartz(): > quartz() > plot( c(0,1), c(0,1) ); > text( 0.5, 0.5, "\u2113" ) # and then File/Save As/ -- David. Begin forwarded message: > From: David Winsemius <dwinsemius at comcast.net> > Date: August 17,

dear R wizards: not important. more a curiosity or esthetics question. is there a way to extend the standard lm command, so that it takes a new argument that handles fixed effects? right now, I have (provided to me from an expert---I would have never figured this one out): diffid <- function(h,id) { id <- as.factor(id)[, drop=TRUE] apply(as.matrix(h), 2, function(x) x

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 wizards: I have a large data frame, a million rows, 40 columns. In this data frame, there are some (about 100,000) rows which I want to recompute (update), while I want to leave others just as is. this is based on a condition that I need to compute, based on what is in a few of the columns. what is the right R way to do this? I could subset out the rows that I want to recompute into a

hi: could someone please point me to a function that allows me to solve general non-linear functions? > irr.in <- function(r, c1, c2, c3 ) { return(c1+c2/(1+r) + c3/(1+r)^2); } > solve.nonlinear( irr.in, -100, 60, 70 ); 0.189 If someone has written an irr function, this would be helpful, too---though not difficult to write, either. thanks for any pointers. Regards, /iaw

dear R wizards: apologies for two queries in one day. I have a long form data set, which identifies about 5,000 regressions, each with about 1,000 observations. unit date y x 1 20060101 <two values> 1 20060102 <two values> ... 5000 20081230 <two values> 5000 20081231 <two values> I need to run such regressions many many times, because they are part of an