similar to: List subsetting

I have a question related to scoping. Suppose we have 2 functions: f1 = function(i){i = 1} f2 = function(n){ i = length(n) f1(i) } In other words, I would like i=1 regardless of n. Is this possible without having f1 in the body of f2? Thanks in advance!

Dear sirs, 1...........Kindly tell me is it possible to form a matrix which contains a no of matrices.. for eg.. if a,b,c,d are matrices.... and e is a matrix which contains a,b,c,d as rows and columns.. 2..........Is it possible to form array of array of arrays for eg.. "A" contains two set of arrays (1,2)...and each A[1] and A[2] individually contains two set of arrays I tried like

Hello. I've observed some odd behaviour. Most likely, it is already known and explained somewhere, but I can't find an explanation anywhere, so I would appreciate being pointed in the right direction. The issue with the following code is self explanatory: > mat <- matrix(c(c(1,1,1),c(2,2,2)),nrow=3) > mat[,c(1:3%/%2)] [,1] [,2] [1,] 1 1 [2,] 1 1 [3,] 1 1

Hi, Does anyone know how to pass a vector of strings, for example "c("1", "2", "3") to a C++ function? Should the input argument to the C++ function be vector<string>*? Thanks a lot! Ivo

Hi. Can anyone suggest a simple way to obtain in R a list of vector coordinates of the following form? The code below is Mathematica. In[5]:= Flatten[Table[{i,j,k},{i,3},{j,4},{k,5}], 2] Out[5]= {{1,1,1},{1,1,2},{1,1,3},{1,1,4},{1,1,5},{1,2,1},{1,2,2},{1,2,3},{1 ,2,4},{1,2, 5},{1,3,1},{1,3,2},{1,3,3},{1,3,4},{1,3,5},{1,4,1},{1,4,2},{1,4,3}, {1,4,

Dear R-ers! I have a badly organized data base in Excel. Once I read it into R it looks like this (all variables become factors because of many spaces and other characters in Excel):

Hi I have two arbitrarily dimensioned arrays, "a" and "b", with length(dim(a))==length(dim(b)). I want to form a sort of "corner-to-corner" version of abind(), or a multidimensional version of blockdiag(). In the case of matrices, the function is easy to write and if a=matrix(1,3,4) and b=matrix(2,2,2), then adiag(a,b) would return: [,1] [,2] [,3] [,4] [,5]

Hi, I usually use optimize function for ML Estimation. Now I?ve got a data frame with many sets, but I can?t save estimates each time I run the code for each data set (I?m using a for loop with my loglikelihood function and works ok but when I apply another for loop to: optimize(my.loglikelihood.function[i], int=c(0.0001,10)) it doesn?t work; alternatively, using optimize inside the for loop

Hello there! My operating system is Windows XP, my version of R is the latest (R-2.5.0). Recently I have downloaded the package "mvtnorm" and a problem with the command "pmvnorm" occured. Trying to enter the lines ... A <- diag(3) A[1,2] <-0.5 A[1,3] <- 0.25 A[2,3] <- 0.5 pvmnorm(lower=c(-Inf,-Inf,-Inf), upper=c(2,2,2),mean = c(0,0,0), corr=A) I got the following

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

thank you, achim. I will try chol2inv. sandwich is a very nice package, but let me make some short suggestions. I am not a good econometrician, so I do not know what prewhitening is, and the vignette did not explain it. "?coeftest" did not work after I loaded the library. automatic bandwidth selection can be a good thing, but is not always. as to my own little function, I like the

Hi List, Here is some example data. myDat <- read.table(textConnection("group id 1 101 1 201 1 301 2 401 2 501 2 601 3 701 3 801 3 901"),header=TRUE) closeAllConnections() corr_mat <-read.table(textConnection("1 1 .5 0 0 0 0 0 0 0 2 .5 1 0 0 0 0 0 0 0 3 0 0 1.0 0 0 0 0 0 0 4 0 0 0 1 .5 .5 0 0 0 5 0 0 0 .5 1

Hi, Suppose I have a multidimensional array: tmp <- array(1:8, c(2,2,2)) is there a function out there that, given a one-dimensional array index, will return the separate indices for each array dimension? for instance, tmp[8] is equivalent to tmp[2,2,2]. I'd like to derive the vector (2,2,2) from the index 8. thanks, Brad Buchsbaum

Hi list, I want to find the total maximum resources I can spend given a set allocation proportion and some simple budget constraints. However, I get suboptimal results via lp and friends (i.e. lpSolve and simplex in the linprog and boot) . For example: library(lpSolve) proportions = c( 0.46, 0.28, 0.26) constraints = c( 352, 75, 171) lp(objective.in = proportions, const.mat =

dear R experts: ?I am writing my own little newey-west standard error function, with heteroskedasticity and arbitrary x period autocorrelation corrections. ?including my function in this post here may help others searching for something similar. it is working quite well, except on occasion, it complains that Error in solve.default(crossprod(x.na.omitted, x.na.omitted)) : system is

Dear R-list member, I'm using the function pmnorm() (-->library(mnormt)) within a for-loop. Certain parameter values leads to an error message: "(In sqrt(diag(S)) : NaNs produced, In sqrt(1/diag(V)) : NaNs produced, In cov2cor(S) : diag(.) had 0 or NA entries; non-finite result is doubtful)" obviously because "NaNs" were produced. Is it possible to tell R that it

Hi This is a difference between the way matrices and data frames work I guess. I want to replace the NA values in a data frame by 0, and the code works as long as the data frame in question actually includes an NA value. If it doesn't, there is an error: df <- data.frame(c1=c(1,1,1),c2=c(2,2,NA)) df[is.na(df)] <- 0 df df <- data.frame(c1=c(1,1,1),c2=c(2,2,2)) df[is.na(df)] <-

Given: > mitest <- matrix(1:16,ncol=4) > dimnames(mitest)[[1]] <- c("a","b","c","d") > dimnames(mitest)[[2]] <- c("a","b","c","d") > mitest a b c d a 1 5 9 13 b 2 6 10 14 c 3 7 11 15 d 4 8 12 16 I can do: > mitest[cbind(c(1,2,3),c(2,3,2))] [1] 5 10 7 but using the names does not

dear r experts---Is there a multicore equivalent of by(), just like mclapply() is the multicore equivalent of lapply()? if not, is there a fast way to convert a data.table into a list based on a column that lapply and mclapply can consume? advice appreciated...as always. regards, /iaw ---- Ivo Welch (ivo.welch at gmail.com)

I am working with some survival data with missing values. I am using the mice package to do multiple imputation. I have found code in this thread which handles pooling of the MI results: https://stat.ethz.ch/pipermail/r-help/2007-May/132180.html Now I would like to plot a survival curve using the pooled results. Here is a reproducible example: require(survival) require(mice) set.seed(2) dt