similar to: stack operations on vectors

summary: Specifically, how does one do stack/FIFO operations in R? Generally, how does one code functions with side effects in R? details: I have been a coder for years, mostly using C-like semantics (e.g., Java). I am now trying to become a scientist, and to use R, but I don't yet have the sense of "good R" and R idiom (i.e., expressions that are to R what (e.g.) the Schwartzian

Is there a package for stacks with pushing and popping? I'd really like to do something like push(par(no.readonly=TRUE)) some stuff.... par(pop()) It seems like it wouldn't be difficult, and that someone may have already implemented a set of stack functions, and I wouldn't like to duplicate it. Thanks for your time, Dave -- Dave Forrest (434)924-3954w(111B) (804)642-0662h

Running R.app on Mac OS X 10.4 > version _ platform powerpc-apple-darwin8.6.0 arch powerpc os darwin8.6.0 system powerpc, darwin8.6.0 status major 2 minor 3.1 year 2006

Running R.app on Mac OS X 10.4 > version _ platform powerpc-apple-darwin8.6.0 arch powerpc os darwin8.6.0 system powerpc, darwin8.6.0 status major 2 minor 3.1 year 2006

I installed the locfit package under Linux (gcc 2.7.2). Installation was ok but > x <- runif(200) > y.compl <- 10*x*x*rgamma(200,3) > med.y <- median(y.compl) > cens <- ifelse(y.compl<=med.y,1,0) > y <- cens * y.compl + (1-cens)*med.y > library(locfit) > m <- locfit(y~x,cens=cens,family="gamma") /usr/local/src/R-0.61.1/bin/R.binary: can't

Dear useRs and wizaRds, I am currently developing a set of functions using S4 classes. On the way I encountered the problem exemplified with the code below. For some reason the 'validity' method does not seem to work, i.e. does not check for errors in the specification of the slots of the defined class. Any hints? My understanding of the whole S4 system was that validity checks are made

This is a simple SSA code generation 101 question. If I follow the IR code generation techniques in the Dragon book the statement x = y + z would translate into something like this in SSA/LLVM %0 = add %y, %z %x = %0 Obviously "copy instructions" like %foo = %bar are senseless in SSA since %foo and %bar are immutably fixed to the same value and there is no need for two aliases

Would introducing the new frame, with the call to local(), cause problems when you use frame counting instead of <<- to modify variables outside the scope of lapply's FUN, I think the frame counts may have to change. E.g., here is code from actuar::simul() that might be affected: x <- unlist(lapply(nodes[[i]], seq)) lapply(nodes[(i + 1):(nlevels - 1)],

From: Daniel Kaschek <daniel.kaschek at physik.uni-freiburg.de> > ... When I evaluate this list of functions by > another lapply/sapply, I get an unexpected result: all values coincide. > However, when I uncomment the print(), it works as expected. Is this a > bug or a feature? > > conditions <- 1:4 > test <- lapply(conditions, function(mycondition){ >

It is my understanding, the alloca memory routines are used for forcing variables to be allocated on the stack frame -- which you would want for source level debugging. When SSA registers are used, LLVM will decide what goes into registers and what will spill over to the stack frame. I want the latter. --w Wayne O. Cochran Assistant Professor Computer Science wcochran at vancouver.wsu.edu

I have an application where I need to preserve object attributes across calls to 'lapply'. The current definition is: lapply <- function (X, FUN, ...) { FUN <- match.fun(FUN) if (!is.list(X)) X <- as.list(X) rval <- .Internal(lapply(X, FUN)) names(rval) <- names(X) return(rval) } Would it make sense to replace names(rval) <- names(X)

> On Feb 24, 2015, at 10:50 AM, <luke-tierney at uiowa.edu> wrote: > > The documentation is not specific enough on the indented semantics in > this situation to consider this a bug. The original R-level > implementation of lapply was > > lapply <- function(X, FUN, ...) { > FUN <- match.fun(FUN) > if (!is.list(X)) > X <-

I'd like to learn the process of revising R functions & packages and then submitting proposed patches to the R Core team. Would someone be willing to mentor me through one example? For starters, consider an example. I'd like to revise the t.test function to return the stderr value to the user. We only need to change the "rval" in the third-from-the end line of

Dear all, I'm using zeroinfl() from the pscl-package for zero inflated Poisson regression. I would like to calculate (aproximate) prediction intervals for the fitted values. The package itself does not provide them. Can this be calculated analyticaly? Or do I have to use bootstrap? What I tried until now is to use bootstrap to estimate these intervals. Any comments on the code are welcome.

Hi! I've noticed the ecdf() R code (R ver. 2.5.0) contains two call to sort: --- [R-code] --- ecdf <- function(x) x <- sort(x) n <- length(x) if (n < 1) stop("'x' must have 1 or more non-missing values") vals <- sort(unique(x)) rval <- approxfun(vals, cumsum(tabulate(match(x, vals)))/n, method

On Fri, Apr 22, 2011 at 10:40 AM, Wayne Cochran <wcochran at vancouver.wsu.edu> wrote: > This is a simple SSA code generation 101 question. > > If I follow the IR code generation techniques in the Dragon book the > statement >  x = y + z > would translate into something like this in SSA/LLVM >  %0 = add %y, %z >  %x = %0 > Obviously "copy instructions"

I am trying to figure out why 'biglm' can handle large data set... According to the R document - "biglm creates a linear model object that uses only p^2 memory for p variables. It can be updated with more data using update. This allows linear regression on data sets larger than memory." After reading the source code below? I still could not figure out how 'update'

I am using an example posted in this help forum to work with a file. the head of the file looks like: 988887 2007-03-05 2007-06-01 90 3 5.450 205500.00 999.00 999.000 0.000 0 0 988887 2007-03-06 2007-06-01 90 3 5.450 205500.00 999.00 999.000 0.000 1 0 988887 2007-03-07 2007-06-01 90 3 5.450 205500.00 999.00 999.000 -0.100 2 0 988887 2007-03-08 2007-06-01 90 3 5.450 205500.00 999.00 999.000 -0.100

Full_Name: Sven Sandin Version: 2.0.0 OS: SuSE Linux 9.0 Submission from: (NULL) (81.227.17.135) Have just compiled and installed R-2.0.0.tar.gz running SuSE9.0. The function vcov do not accept "coxph" object as input any longer. The same R-program running R1.9.1 do work. R-program attached below. Exporting the coxph object from R2.0.0 to R1.9.1 I get vcov ouput in R1.9.1. Exporting

I am looking for a function in R that is equivalent to the function "peaks" in Splus. This function gives the local maxima of a vector. I do not find it using the help and I 'm not sure it exits in R. Could someone help me ? Thanks, Herve Cardot -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read