similar to: model.frame and parent environment

Brian, So let me ask an r-core opinion. Should I change the default to model=TRUE? Survival is heavily used and there is something to be said for consistency within the central packages. Sometimes old habits die hard, and there is a "save memory" part of me that hates to save a large object that likely won't be used. Not nearly as relevant today as when I started my

I've narrowed my scope problems with predict.coxph further. Here is a condensed example: fcall3 <- as.formula("time ~ age") dfun3 <- function(dcall) { fit <- lm(dcall, data=lung, model=FALSE) model.frame(fit) } dfun3(fcall3) The final call fails: it can't find 'dcall'. The relevant code in model.frame.lm is: env <- environment(formula$terms)

The replies so far have helped me see the issues more clearly. Further comments: 1. This issue started with a bug report from a user: library(survival) fform <- as.formula(Surv(time, status) ~ age) myfun <- function(dform, ddata) { predict(coxph(dform, data=ddata), newdata=ddata) } Gabor's suggestion to change the call is a useful idea but not completely relevant: I'm

Thanks for the reproducable example. I can confirm that it fails on my machine using survival 2-37.5, the next soon-to-be-released version, The issue is with NextMethod, and my assumption that the called routine inherited everything from the parent, including the environment chain. A simple test this AM showed me that the assumption is false. It might have been true for Splus. Working this

I recently began hacking around with my first LLVM pass. The big picture is that I would like to insert function calls for each instruction type, and pass some parameters based on the instruction type. Then I will link the output to some C file that implements those functions. Things were going well until I started trying to make function calls with a pointer as a parameter. For example, I would

Hello, If the signature of a method defines which generic it implements then I'm confused about why this minimal example I invented won't work : setGeneric("myFun", function(rs, ...){standardGeneric("myFun")}) setGeneric("myFun", function(cs, ...){standardGeneric("myFun")}) setMethod("myFun", "numeric", function(rs, colour =

I declared the environment of the function myfun to be NULL as follows: environment(myfun) <- NULL Later on I called that myfun and got an error message because the function index() in the zoo package was called inside myfun and was not visible: Error in myfun(args) : couldn't find function "index" I tried to use zoo::index() instead of index(), but that did not work. In fact,

Dear R useRs, I have a problem with nls.lm function of minpackl.lm package. I need to fit the Van Genuchten Model to a set of data of Theta and hydraulic conductivity with nls.lm function of minpack.lm package. For the first fit, the parameter estimates keep changing even after 1000 iterations (Th) and I have a following error message for fit of hydraulic conductivity (k); Reason for

Dear Rers, I have a function to barplot() a matrix, eg myfun <- function(x, ...) { barplot(x , ... )} (The real function is more complicated, it does things to the matrix first.) So I can do: m1 <- matrix(1:20,4) myfun(m1) myfun(m1, main="My title") I'd like to be able to add the number of rows of the matrix passed to the function to the "..." argument, eg

Hello R users, i'm wondering how to trigger variable creation. Whenever a variable is created i want my own function myFun(...) to be started. if (exists("x")) {rm(x)} # after removal of x # any of these calls x<-10 # should call myFun x=10 # should call myFun assign(x,10) # should call myFun etc.

Of course (and unsurprisingly) Duncan is correct. I see that behavior in R 3.1.0, as well as the modern ones Duncan mentioned. What I said is true, as far as it goes, but the symbol being resolved is FUN, so when looking for a function it doesn't find the function version of round. Did you perhaps have a function named FUN in your global environment? If so you are being bitten by what I

R> myfun <- function(x, ...) {x[...] <- 0; x} R> myfun(3) Error in myfun(3) : SubAssignArgs: invalid number of arguments It fails because no ... was passed. The workaround (and desired behavior) is: R> myfun <- function(x, ...) {if (missing(...)) x[] <- 0 else x[...] <- 0; x} R> myfun(3) [1] 0 Deja vu? This is the one piece of my PR#1110 (Oct 3, 2001) that I

Is there a way to call a function, and explicitly set an argument to 'not specified'? My situation is the following. I have a function which passes on most of its arguments to another function. The second function, myfun2, serializes all arguments and is out of my control. myfun <- function(...){ return(myfun2(...)); } now, the value for arguments of myfun are stored in variables.

Hi, on R version 2.15.1 (2012-06-22) (Platform: i686-pc-linux-gnu (32-bit)) sourced functions have srcref attached as an attribute. Are such data also available for S4 generics and methods? How? (See sample code below) Thank you. Bests, Renaud f <- textConnection( " f <- function(){} setGeneric('myfun', function(x, ...) standardGeneric('myfun'))

Hi, this is a made-up example. Function "myfun" returns two arguments. Can "apply" be used so that "myfun" is called only once? Thanks Serguei mat<-matrix(runif(50),nrow=10,ncol=5) myfun<-function(x) { mymean<-mean(x) mysd<-sd(x) return(mymean,mysd) } out1<-t(apply(mat,1,function(x) myfun(x)$mymean)) out2<-t(apply(mat,1,function(x)

Hi, I have a function myFun which I want to call multiple times, using different argument lists. myFun("v1", "2009", 1) myFun("v2", "2008", 1) myFun("q", "2001") How can I easily do this in R? Should I use mapply? I unsuccessfully tried something like: x <- list(c("v1", "2009", 1), c("v2",

> -----Original Message----- > From: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Michael > Sent: Thursday, April 20, 2006 3:50 AM > To: R-help at stat.math.ethz.ch > Subject: [R] Bootstrap error message: Error in > statistic(data, original, ...) : unused argument(s) ( ...) [Broadcast] > > > Dear colleagues, >

Dear all, I have used optim a lot in contexts where it would useful to be able to iterate function myfun that, in addition to the primary objective to be minimized ('minimize.me'), could return other values such as alternative metrics of the minimization, informative intermediate values from the calculations, etc. myfun <- function() { ... return(list(minimize.me = minimize.me, R2 =

I don't understand how this function can subset by i when i is missing.... ## My function: myfun = function(vec, i){ ret = vec[i] ret } ## My data: i = 10 vec = 1:100 ## Expected input and behavior: myfun(vec, i) ## Missing an argument, but error is not caught! ## How is subsetting even possible here??? myfun(vec) Is there a way to check for missing function arguments, *and*

Suppose I have the following function myFun <- function(formula, data){ f <- formula(formula) dat <- model.frame(f, data) dat } Applying it with this sample data yields a new dataframe: qqq <- data.frame(grade = c(3, NA, 3,4,5,5,4,3), score = rnorm(8), idVar = c(1:8)) dat <- myFun(score ~ grade, qqq) However, what I would like is for the resulting dataframe (dat) to include