similar to: plyr package: passing further arguments fail

I have a general style question about R coding. Suppose I'm writing a function (foo1) that calls other functions (foo2, foo3, ...) which have complicated argument lists (e.g. optim(), plot()), _and_ I may be calling several different functions in the body of foo1. Since foo2 and foo3 have different sets of arguments, I can't just use "..." ; I did write some code a while ago

Dear list, I'm stuck with looking for a function of the *apply family, which I suppose exists already ? just I can't find it: What I'm looking for is somewhere between sweep and mapply that does a calculation vectorized over a matrix and a vector: It should work complementary to sweep: for each row of the matrix, a different value of the vector should be handed over. Close to

This script below pulls yahoo data via a function in quantmod, then massages the data around to forumalate a 3D graph with RGL library, attached is a ggplot to show the data i'm trying to create a surface with in separate line geoms . the issue is that the 3D graph looks very ugly and cut up because of the limited quantities of points on the front month expirations.. can anyone tell me whats

Dear list members, Any help on this efficiency issue would be greatly appreciated. I would like to find the most efficient way to run a non-vectorized function (here: fisher exact test p-value) iteratively using 4 matrices with identical dimensions. And as a result I aim for an array with identical dimensions containing the corresponding p-values. Please consider some code using a trivial

--KsGdsel6WgEHnImy Content-Type: text/plain; charset=iso-8859-1; format=flowed Content-Disposition: inline Content-Transfer-Encoding: 8bit Hi, people. Wandering in R archives, and seeing the message attached below, I noticed that: mapply(rep,times=1:4, MoreArgs=42) still segfaults on R 2.2.0, and thought I should be a good citizen and report it, even if I do not have an actual problem

plyr is a set of tools that solves a common set of problems: you need to break a big problem down into manageable pieces, operate on each pieces and then put all the pieces back together. It's already possible to do this with split and the apply functions, but plyr just makes it all a bit easier with: * consistent names, arguments and outputs * input from and output to data.frames,

plyr is a set of tools that solves a common set of problems: you need to break a big problem down into manageable pieces, operate on each pieces and then put all the pieces back together. It's already possible to do this with split and the apply functions, but plyr just makes it all a bit easier with: * consistent names, arguments and outputs * input from and output to data.frames,

Dear all, I'm puzzled by the following example inspired by a recent question on R-help, cc <- textConnection("user_id website time 20 google 0930 21 yahoo 0935 20 facebook 1000 25 facebook 1015 61 google 0940") d <- read.table(cc, head=T) ; close(cc) table(d$user_id) # count the

Let's say I have, for some reason, a bunch of scalars (i.e. single-valued variables) and I want to merge them all into a single vector of values. Can someone recommend a better function, or simpler way, to do so than the following? Suppose my scalars' names are foo1, foo2, foo3, foo1high, foo2high, foo3lo2, etc. Then I can do: >ls(pat='foo')->thels

Dear List: In short, I am writing a number of functions as building blocks for other functions and have some questions about scoping and passing arguments. Suppose I have functions foo1, foo2, and foo3 such that: foo1<-function(a=1,b=TRUE,c=FALSE){#do stuff}; foo2<-function(x=1,y=FALSE,z=c(1,2,3,4)){#do stuff}; foo3<-function(lambda,...){lambda*foo1()*foo2()}; I want to be able to

Hello everybody. I've been experimenting with mapply(). Does anyone else have problems with: R> mapply(rep,times=1:4, MoreArgs=42) (I get a seg fault). robin R> R.version _ platform powerpc-apple-darwin6.6 arch powerpc os darwin6.6 system powerpc, darwin6.6 status beta major 1 minor 8.0 year 2003 month 10 day 02 language R >

I'm trying to use Rprof() to identify bottlenecks and speed up a particullary slow section of code which reads in a portion of a tif file and compares each of the values to values of predictors used for model fitting. I've written up an example that anyone can run. Generally temp would be a section of a tif read into a data.frame and used later for other processing. The first portion

Hi All I have regression coefficients from an experiment and I want to plot them in lattice using panel curve but I have run into error messages. I want an 3 panel conditioned plot of 2 curves of Treatment 2 in each panel conditioned by Treatment1, the example curve expression is x+value*x^2 A rough toy example to give an idea of what I want is: Data: data = expand.grid(Treatment1 =

Hi, Here are the issues I found: Typos ----- (a) Found: It a parallel version of ?evalq?, "is" missing. (b) Found: 'parLapplyLB', 'parSapplyLB' are load-balancing versions, intended for use when applying ?FUN? to 'parLapplyLB' has no 'FUN' arg (more on this below). (c) Found: 'clusterApply' calls 'fun' on the first

Hi, R users, Here is an example. k <- c(1,2,3,4,5) i <- c(0,1,3,2,1) if k=1, then i=0 if k=2, then i=0, 1 if k=3, then i=0, 1, 2, 3 if k=4, then i=0, 1, 2 if k=5, then i=0, 1 so i'd like to create a list like below. > list k i 1 1 0 2 2 0 3 2 1 4 3 0 5 3 1 6 3 2 7 3 3 8 4 0 9 4 1 10 4 2 11 5 0 12 5 1 I tried expand.grid, but I can't. Any suggestion will be

I think need to do something like this: dat<-data.frame(state=sample(id=rep(1:5,each=200),1:3, 1000, replace=T,prob=c(0.7,0.05,0.25)),V1=runif(1,10,1000),V2=rnorm(1000)) rle.dat<-rle(dat$state) temp<-1 out<-data.frame(id=1:length(rle.dat$length)) for(i in 1:length(rle.dat$length)){ temp2<-temp+rle.dat$length[[i]] out$V1[i]<-mean(dat$V1[temp:temp2])

Hello! I have noticed that mapply() drops names in R 2.3.1 as well as in r-devel. Here is a simple example: l <- list(a=1, b=2) k <- list(1) mapply(FUN="+", l, k) [1] 2 3 mapply(FUN="+", l, k, SIMPLIFY=FALSE) [[1]] [1] 2 [[2]] [1] 3 Help page does not indicate that this should happen. Argument USE.NAMES does not have any effect here as it used only in a bit special

Dear expeRts, I am trying to wrap up a package "utilities" (for my internal use). After adding a function datNAtreat that uses mapply, R CMD check gives WARNINGs for "S3 generic/method consistency", "checking replacement functions" and?"checking foreign function calls", all of which are accompanied by the following error message: Error in .try_quietly

Dear all I know that the R way of documenting things is to work on your project in package development mode, and document each object (such as data frames) in a *.Rd files. This should work for gurus. What about a simpler way to document things, geared for mere mortals? I was thinking of a label() or tag() function that could store and retrieve an alphanumeric comment for a given object (for

I have a data frame called e, dim is 27,3, the first 5 lines look like this: V1 V2 V3 V4 1 1673 0.36 0.08 Smith 2 167 0.36 0.08 Allen 3 99 0.37 0.06 Allen 4 116 0.38 0.07 Allen 5 95 0.41 0.08 Allen I am trying to calculate the proportion/percentage of V1 which would have values >0.42 if V2 was the mean of a normal distribution with V1