search for: ivowel

dear r-experts: there is probably a very easy way to do it, but it eludes me right now. I have a large data frame with, say, 26 columns named "a" through "z". I would like to define "sets of regressors" from this data frame. something like myregressors=c("b", "j", "x") lm( l ~ myregressors, data=... ) is the best way to create new

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: 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---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 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---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

dear r-experts: I need to speed up my monte-carlo simulations. my code is written in R (and it was also the cause of my many questions here over the last few days). my code is almost all matrix/vector algebra on panel data sets---long-difference, fixed-effects, blundell-bond, etc.. the data set is about 10MB, so 1GB per CPU core should be plenty for my operations, and with $10/GB of

Dear R Experts--- Sorry for all the questions yesterday and today. I am trying to use Yves Croissant's pgmm function in the plm package with Blundell-Bond moments. I have read the Blundell-Bond paper, and want to run the simplest model first, d[i,t] = a*d[i,t-1] + fixed[i] + u[i,t] . no third conditioning variables yet. the full set of moment conditions recommended for system-GMM,

just a short beg for the next R 2.3 version: I know it is easy to add the sd into summary() in the source bowels of R---but everytime R is updated, my change disappears. :-(. I do not believe that R has an easy extension mechanism for univariate summaries, short of a function rewrite here. Could this please be added into R 2.3? Aside, a logical ordering might also be: mean sd min q1 med q3

Dear R wizards: sorry to bug everyone twice in one day. I would like to annotate my graph by putting text strings into rectangle boxes with a little cartoon-like bubble with a lid pointing to a specific location. I can draw some sort of bubble-with-lid using the R primitives. (has anyone done something like this already?) the problem where I am stuck is that the width of the rectangle must

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 experts: I am trying to plot an empirical likelihood function in 3d. The values are not over a regular grid---I just searched the likelihood function to find the optimal value, and then computed a few values around it. (each point in the likelihood function takes a very long time to compute.) the likelihood values now sit in a csv file that has three columns, "mu",

dear R experts: does R have "static" variables that are local to functions? I know that they are usually better avoided (although they are better than globals). However, I would like to have a function print how often it was invoked when it is invoked, or at least print its name only once to STDOUT when it is invoked many times. possible without <<- ? sincerely, /iaw

some hints for the search engines. I just did install.packages("foreach") install.packages("doMC") library(doMC) registerDoMC() library(foreach) > foreach(i = 1:3) %dopar% sqrt(i) The process has forked and you cannot use this CoreFoundation functionality safely. You MUST exec(). Break on

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 experts--- t <- 1:30 f <- function(t) { cat("f for", t, "\n"); return(2*t) } g <- function(t) { cat("g for", t, "\n"); return(3*t) } s <- ifelse( t%%2==0, g(t), f(t)) shows that the ifelse function actually evaluates both f() and g() for all values first, and presumably then just picks left or right results based on t%%2.

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 group: I have the probably fairly common problem that I would like to have one code.R file do different things if it is invoked from a symbolic link, which should be easy to uncover. $ ln -s code.R code-0.R $ ln -s code.R code-1.R $ R CMD BATCH code-1.R what needs to be in code-1.R to put code-1.r into a character vector? help appreciated. regards, /ivo welch PS : I read

I wonder if this is an intentional feature or an oversight. in some column summaries or in ifelse operations, apparently I am losing the date property of my vector. > a <- c(198012, 198101, 198102) > b <- a*100+31 > c <- as.Date( as.character(b), "%Y%m%d" ) > summary(c) Min. 1st Qu. Median Mean 3rd Qu. Max.