similar to: Using apply to generate matrix from rows?

Dear all, sorry, this is for sure really basic, but I searched a lot in the internet, and just couldn't find a solution. The problem is to create new variables from a data frame which contains both individual and group variables, such as mean age for an household. My data frame: df hhid h.age 1 10010020 23 2 10010020 23 3 10010126 42 4 10010126 60 5 10010142

Dear all, I'm running a self-written numerical optimization routine (hazard model) which includes computing the inverse of the outer product of the score. I have been getting the above error message ("System is computationally singular"), and after some tweaking, I realized that these variables have some high numbers and the problem could be circumvented by scaling them down (i.e.

Hi everyone, I would like to compute the sum of cross products of rows of a matrix. Does anyone know how to do this without an explicit loop for computational efficiency? Below is a code example. Thanks! Stephan # I.e., if I have a matrix like this x <- matrix(rep(c(1,2,3),3),ncol=3) ## > x ## [,1] [,2] [,3] ## [1,] 1 1 1 ## [2,] 2 2 2 ## [3,] 3 3

Dear all, I have a code where I subset a data frame to match entries within levels of an factor (actually, the full script uses three difference factors do do that). I'm very happy with the precision with which I can work with R, but since I loop over factor levels, and the data frame is big, the process is slow. So I've been trying to speed up the process using by(), but I got stuck at

Dear all, A quick question which I somehow cannto figure out: I want to apply the function "any" to subsets of a dataset in order to create a vector with TRUE/FALSE values, depending on whether a subset has the number 5. I.e., y <- matrix(c(1,2,3,3,4,5,5,6,6,7,5,1,1,3,5,NA,5,1,1,3),ncol=2) > y [,1] [,2] [1,] 1 5 [2,] 2 1 [3,] 3 1 [4,] 3 3 [5,]

I keep getting the 'memory.size' error message when I run a program I have been writing. It always it cannot allocate a vector of a certain size. I believe the error comes in the code fragement below where I have multiple arrays that could be taking up space. Does anyone know a good way around this? w1 <- outer(xk$xk1, data[,x1], function(y,z) abs(z-y)) w2 <- outer(xk$xk2,

Consider a data frame (x) with 2 variables, x1 and x2, having equal values. It looks like: x1 x2 1 1 2 2 3 3 Now, consider a second data frame (xk): xk1 xk2 0.5 0.5 1.0 0.5 1.5 0.5 2.0 0.5 0.5 1 1.0 1 1.5 1 2.0 1 0.5 1.5 1.0 1.5 1.5 1.5 2.0 1.5 0.5 2 1.0 2 1.5 2 2.0 2 I have written code to calculate some differences between these

Dear all, I'm trying to import a csv file into sqlite3 and from there into R. Everything looks fine exepct that R outputs the character values in an odd fashion: they are shown as "\"CHARACTER\"" instead of "CHARACTER", but only if I show the character variable as a vector. Does someone know why this happens? Below is a sample code. The first part is written in

useR's, I am trying trying to find out if there is a faster way to do a certain computation. I have successfully used FOR loops and the apply function to do this, but it can take some time to fully compute, but I was wondering if anyone may know of a different function or way to do this: > x [1] 1 2 3 4 5 > xk [1] 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 I want to do:

Dear expe-R-ts, I try some test data for a factorAnalysis (resp. pca) in the sense of Prof. Ripley's MASS ? 11.1, p. 330 ff., just to prepare myself for an analysis of my own empirical data using R (instead of SPSS). 1. the data. ## The test data is (from the book of Backhaus et al.: Multivariate ## Analysemethoden. Springer 2000 [9th ed.], p. 300 ff):

Hi. I'd like to find some way for Samba to convert the filenames created by Macintosh OS X into something windows can use. According to their docs: http://developer.apple.com/techpubs/macosx/Essentials/SystemOverview/FileSystem/chapter_9_section_13.html filenames are stored as canonically decomposed Unicode 2.1 in UTF-16 format (a sequence of 16-bit codes) Samba running on a

Dear all, just a quick question regarding weights in logistic regression. I do results <- lrm(y.js ~ h.hhsize + h.death1 + h.ill1 + h.ljob1 + h.fin1 + h.div1 + h.fail1 + h.sex + h.ch.1

Dear all, I'm trying to select from a dataframe all rows which correspond to a factor (the id variable) for which there exists at least one positive value of a certain variable. As an example: x <- data.frame(matrix(c(rep(11,4),rep(12,3),rep(13,3),rep(0,3),1,rep(0,4),rep(1,2)),ncol=2)) > x X1 X2 1 11 0 2 11 0 3 11 0 4 11 1 5 12 0 6 12 0 7 12 0 8 13 0 9 13 1 10

I'm trying to make multiple line plots, each with a different color, using the xyplot command. Specifically, I have an NxK matrix Y and an Nx1 matrix x. I would like the plot to contain a line for each (x, Y[,i]), i=1:K. I know something like xyplot(Y[,1] + Y[,2] + Y[,3] ~ x, type='l') will work, but if Y is large, this notation can get very awkward. Is there a way to do something

i was using multiple ports because that's how i figured i'd have to do it. o, mounting the remote source locally? i'm not familiar with how to do this. i'm also not seeing how to do this in the docs. how would i go about mounting a remote stream? -a.j. On Fri, 27 Apr 2001, Jack Moffitt wrote: > Why are you using multiple ports at all? That's what mountpoints are >

useR's, I would like to know if there is a way to avoid using FOR loops to perform the below calculation. Consider the following data: > x [,1] [,2] [,3] [1,] 4 11 1 [2,] 1 9 2 [3,] 7 3 3 [4,] 3 6 4 [5,] 6 8 5 > xk Var1 Var2 Var3 1 -0.25 1.75 0.5 2 0.75 1.75 0.5 3 1.75 1.75 0.5 4 2.75 1.75 0.5 5 3.75 1.75

I have the following problem. Consider a `classical' test which works for k .ge. 2 samples. Possible interfaces are e.g. xxx.test(x, g) x ... all data, g ... corresponding groups xxx.test(x1, ..., xk) xxx.test(list(x1, ..., xk)) etc etc. Clearly, the first and the second one are nice, but cannot be combined without making `g' (i.e., `group') a named argument. Hence, in

I'm pulling my hair (and there's not much left!) on this one. Basically I'm not getting the same result t when I "step" through the program and evaluate each element separately than when I use the outer() function in the FindLikelihood() function below. Here's the functions: Dk<- function(xk,A,B) { n0 *(A*exp(-0.5*(xk/w)^2) + B) } FindLikelihood <-

Dear readers of the list, I have a problem a comparison of two data from a vector. The comparison yields FALSE but should be TRUE. I have checked for mode(), length() and attributes(). See the following code (R2.10.0): ----------------------------------------------- # data vector of 66 double data X =

Hi, I have tried to install 'tensor' as a new package in these phases: 1. via 'Install package from local Zip-File' in Rgui/Windows98: install.packages("D:/R/_Pakets12MB/tensor.zip", .lib.loc[1], CRAN = NULL) 2. Looking at the library folder, there was now a new entry 'tensor' including some files e.g. \library\tensor\R\tensor.R 3. Then I have done