similar to: pass-by-reference

I'm getting the following form R CMD CHECK mypackage ----------- * checking Rd files ... WARNING Error in Rd[[which]] : subscript out of bounds problem found in ?myfunction.Rd? --------- This is... not the most helpful error. I'd be happy to make a minimal .Rd example file if someone can point me to what a minimal .Rd file has in it. The file is already pretty minimal, so it's

Hi, I'm trying to make a new S4 object with a slot for a "link-glm" object. R doesn't like me have a slot of class "link-glm" > class(make.link("probit")) [1] "link-glm" > setClass("a",representation(item="link-glm")) [1] "a" Warning message: undefined slot classes in definition of "a": item(class

Full_Name: Paul Bailey Version: 2.1.1 OS: OS X 10.3 Submission from: (NULL) (68.252.250.144) ?cor [tells me that it has a na.rm variable] > cor(frame2[1,],frame2[2,],na.rm=T) Error in cor(frame2[1, ], frame2[2, ], na.rm = T) : unused argument(s) (na.rm ...) hmm.

I'm having a problem with aggregate.formula when I call it in a function and the function is converted from a string in the funtion I think my problem may also only occur when the left hand side of the formula is cbind(...) Here is example code that generates a dataset and then the error. The first function "agg2" fails > agg2(FALSE) do agg 2 Error in m[[2L]][[2L]] : object

Hi, I wonder how to pass several functions and their arguments as arguments to a function. For example, the main function is f = function(X ) { process1(X) ... process2(X) } I have a few functions that operate on X, e.g. g1(X, par1), g2(X, par2), g3(X, par3). par1, par2 and par3 are parameters and of different types. I would like to pass g1, g2, g3 and their arguments to f and g1,

I'm solving 4 complex equations simultaneously. Code is below. The code returns only zero's for the solution though there should also be a non-zero result. I'm pretty confident that the equations are correct because they are straight from a published paper and I checked them pretty thoroughly. The parameter values I used are from the published paper as well. Any suggestions for how

Dear R-list, I would like to use the lattice library to show several groups on the same graph. Here's my example : ## the data f1 <- factor(c("mod1","mod2","mod3"),levels=c("mod1","mod2","mod3")) f1 <- rep(f1,3) f2 <-

I define the following function: (Please don't wonder about the use of this function, this is just a simplified version of my actual function. And please don't spend your time in finding an alternate way of doing the same as the following does not exactly represent my function. I am only interested in a good explanation) > f1 =

Hi R-devel. Is the following behavior in g1() and h1() expected? It seems to make "..." arguments work slightly differently from named arguments. #missing() has the property that it looks "up the chain" #for example, "z" can be missing in f3 even if #that argument did have a name ("y") in f2 f1 <- function(x, ...) { cat("In f1, missing(x) is

#I have a data set that looks like this. A bit more complicated actually with # three factor levels but these calculations need to be done on one factor at a #I then have a set of different rates that are applied #to it. #dataset cata <- c( 1,1,6,1,1,2) catb <- c( 1,2,3,4,5,6) doga <- c(3,5,3,6,4, 0) data1 <- data.frame(cata, catb, doga) rm(cata,catb,doga) data1 # start rates #

Hi, I run this code to get the power of the test for modified bartlett's test..but I'm not really sure that my coding is right.. #normal distribution unequal variance asim<-5000 pv<-rep(NA,asim) for(i in 1:asim) {print(i) set.seed(i) n1<-20 n2<-20 n3<-20 mu<-0 sd1<-sqrt(25) sd2<-sqrt(50) sd3<-sqrt(100) g1<-rnorm(n1,mu,sd1) g2<-rnorm(n2,mu,sd2)

Hi, I'm having difficulty coming up with a good way to subest some data to generate statistics. My data frame has multiple observations by group. Here is an overly-simplified toy example of the data ========================== code v1 v2 G1 1.2 2.3 G1 0 2.4 G1 1.4 3.4 G2 2.9 2.3 G2 4.3 4.4 etc.. ========================= I want to normalize the data *by group* for certain variable.

Hi, I have a column (V4) in a midi event list which includes tone pitch names, i.e. "A4, E4, C#4, A3...": > compo[1:10,] V1 V2 V3 V4 V5 V6 V7 1 1 1 0 A4 96 2 0 2 1 1 0 E4 96 2 0 3 1 1 0 C#4 96 2 0 4 1 1 0 A3 96 2 0 5 1 3 0 B4 96 1 0 6 1 3 0 E4 96 1 0 7 1 3 0 B3 96 1 0 8 1 3 0 G#3 96 1 0 9 1 4 0 C#5 96 1 0 10

Dear R helpers,   Following is a R script I am using to run the Fast Fourier Transform. The csv files has 10 columns with titles m1, m2, m3 .....m10.     When I use the following commands, I am getting the required results. The probelm is if there are 100 columns, it is not wise to define 100 commands as fk <- ONS$mk and so on. Thus, I need some guidance to write the loop for the STEP A and

Evening, I was writing some code that tried to insert calls to the llvm.annotation intrinsic function, which has a signature of (i32, i8*, i8*, i32). The code is below. void addAnnotation( BasicBlock *block, Function *F) { string foo = "foo"; string bar = "barr"; Type *charTy = Type::getInt8Ty(block->getContext()); ArrayType *s1Ty =

Hello all, In order to get the desired order of panels within lattice I realized I needed to define my factor levels. I now see how to properly do it (attached code), but: 1. I don't understand why I have to use factor() on a variable that is already a factor, and why levels() alone doesn't work to readjust the level order. 2. I just noticed that if I do use levels(xx$v1), it's

Andrew Ruef wrote: > Evening, > > I was writing some code that tried to insert calls to the > llvm.annotation intrinsic function, which has a signature of (i32, > i8*, i8*, i32). The code is below. > > void addAnnotation( BasicBlock *block, Function *F) > { > string foo = "foo"; > string bar = "barr"; > > Type

Hi, I want to compute a distribution of the intersection of a graph and 'randomized' graphs induced by the permutations of node labels (to preserve the graph topology). Since I ll have many permutations to perform, I was thinking of using the snow package and in particular "parSapply" to divide the work between my 4 CPUs. But I get the following error message : Error in

Hi, John I am building a flow sensitive intra-procedural alias analysis(without interprocedural info). So, the first thing I have to consider is where a parameter-pointer or a global-pointer might point to. Then I defined several special Virtual Memory Locations: ALL_MEMORY, GLOBAL_MEMORY, STACK_MEMORY, HEAP_MEMORY. ALL_MEMORY contains GLOBAL_MEMORY, STACK_MEMORY, HEAP_MEMORY. e.g1:

Dear R users, I am trying to fit an lmer model with only random effects which is giving me the following error: Error : length(f1) == length(f2) is not TRUE In addition: Warning messages: 1: In P1L55:family : numerical expression has 390 elements: only the first used 2: In P1L55:family : numerical expression has 390 elements: only the first used I am trying to extract variance components