similar to: Recycling Rule

Why anything but sweep? The fundamental data type in Matlab is a matrix... they don't have vectors, they have Nx1 matrices and 1xM matrices. Vectors don't have any concept of "row" vs. "column". Straight division is always elementwise with recycling as needed, and matrices are really vectors in row-major order: 1 2 3 4 5 6 is really 1 4 2 5 3 6 and when you do

Is there a better way to express operations between matrices and column vectors than transposing the matrix twice? This is the kind of thing I'm talking about: m = matrix(1:20, 3, 4) v = colSums(m) t(t(m) / v) ## <-- kinda ugly, ain't it? I thought of converting the column vector to a matrix: m / matrix(v, nrow = nrow(m), ncol = length(v), byrow = TRUE) But that seems even

Hi I had a hard-to-find bug in some of my code the other day, which I eventually traced to my misusing of sweep(). I would expect sweep() to give me a warning if the elements don't recycle nicely, but X <- matrix(1:36,6,6) sweep(X,1,1:5,"+") [,1] [,2] [,3] [,4] [,5] [,6] [1,] 2 9 16 23 30 32 [2,] 4 11 18 25 27 34 [3,] 6 13 20 22

The rules for conformability of objects required for various operators remain a mystery as do some related problems like the rules for recycling in creating arrays etc. Would someone be able to direct me to where such rules are stated? In a related vein, there are all manner of operations that are readily coded in Gauss or in MATA that fail, often mysteriously, in R. Are there some

I am trying to generate a fourth vector,z, given three known and fixed vectors, x1,x2,x3 with corresponding known and fixed correlations with themeselves and with z. That is, all correlations are known and prespecified. How can I do this? Thank you, ben

I decided to do a direct comparison of transpose and sweep. library(microbenchmark) NN <- matrix(c(1, 2, 3, 4, 5, 6), nrow = 2, byrow = TRUE) # Example matrix lambda <- c(2, 3, 4) # Example vector colNN <- t(NN) microbenchmark( sweep = sweep(NN, 2, lambda, "/"), transpose = t(t(NN)/lambda), colNN = colNN/lambda ) Unit: nanoseconds expr min lq

I am having a hard time understanding just what 'sweep' does. The documentation states: Return an array obtained from an input array by sweeping out a summary statistic. So what does it mean "weeping out a summary statistic"? Thank you. Kevin

Hi, I've got an array, say with i,jth entry = A_ij, and a vector, say with jth entry= v_j. I would like to multiply each column of the array by the corresponding vector component, i,e. find the array with i,jth entry A_ij * v_j This seems so basic but I can't figure out how to do it without a loop. Any suggestions? Michal.

I am currently trying to transpose some large panel data set ie transposing multiple rows in into a single column. instead the transpose functionality transposes all rows into columns. my sample data set looks like below: ACCT_NUM ACCOUNT_NAME TRAN_AMT DATE EMPLOYER 101913 GK 7489 30-Apr-10 PENSION 101913 GK 7489 30-May-10 PENSION 101913

Hi I want to use R's recycling rule. At the moment I am using the following: x <- c(1, 2, 3) n <- 10 ## so using the recycling rules, I would like to get from FUN(x, n)==1 ## I am doing: xRecycled <- rep(x, length.out=n)[n] This works, but it seems to me that I am missing something really basic here - is there more straightforward way of doing this? Cheers, Rainer -- NEW

Does anyone have any information on how to use DUNDi precaching? Mark Spencer made a post 2 years ago where he hinted it may be possible to configure DUNDi such that you could centralise your DUNDi registration info by using precaching, instead of having each DUNDi peer meshed with every other one... http://lists.digium.com/pipermail/dundi/2004-October/000189.html However, it seems that no

I am a bit confused about the different approaches taken to recycling in plain data frames and zoo objects. When carrying out simple arithmetic, dataframe seem to recycle single arguments, zoo objects do not. Here is an example > x <- data.frame(a=1:5*2, b=1:5*3) > x a b 1 2 3 2 4 6 3 6 9 4 8 12 5 10 15 > x$a/x$a[1] [1] 1 2 3 4 5 > x <- zoo(x) > x$a/x$a[1] 1 1 >

Hi, Can I rotate a plot (e.g. a distribution plot) by 90 degrees? The barplot function provides the "horiz" command but that's not availeable for the base package functions. I found an old advice from Paul Murrell on a similar problem suggesting to use viewports (grid package). Yet I couldn't reproduce his examples successfully. And going through the examples in the current grid

I have a dataset in "long" format that looks something like this: ID TEST RESULT 1 A 17 1 A 12 1 B 15 1 C 12 2 B 8 2 B 9 Now what I would like to do is transpose it like so: ID TEST A TEST B TEST C 1 17 15 12 1 12 . . 2

Hi, I'm an R beginner and I'm struggling with what should be a rudimentary task. My data is along these lines: ID name1 name2 name3 name4 Class 0 1 0 2 Var1 A B C A Var2 B C C A Var3 C A B A etc. I'm using the following: foo <- data.frame(t(read.table("file", header=FALSE))) but of course now it's not using ID, Class, etc. as column names. As you can imagine,

I've dug around but not been able to find anything, am probably missing something obvious. How can I fill a three-dimensional (or higher dimension) array by rows instead of columns. eg new1 <- array(c(1:125), c(5,5,5)) works fine for me but fills it by columns and new2 <- array(c(1:125), c(5,5,5), byrow=TRUE) throws an error. Am I missing something obvious? I also tried

So, trying to convert a very long, somewhat technical bit of lin alg MATLAB code to R. Most of it working, but raninto a stumbling block that is probaably simple enough for someone to explain. Basically, trying to 'line up' MATLAB results from an element-wise division of a matrix by a vector with R output. Here is a simplified version of the MATLAB code I'm translating: NN = [1,

Thanks to everyone who has replied to my emails so far - to summarise: AIX allows setting of rlogin=false and and a su group, or a list of users that are permitted to "su" to root. ( or other functional ids ) This means with entries in /etc/ftpusers, it is possible to : 1/ Track who used root via sulog and or external logging 2/ Protect root even if the root password is compromised 3/

hi all i have a simple question. code is displayed below. how can i use a vectorised command in order to do this (ie replace the loop)? (ie apply, lapply, sweep, etc) z<-matrix(c(1:9),3,3) top<-c(1.5,5.5,9) for (i in 1:3) z[z[,i]>top[i]]<-top[i]

Greetings all, I am having difficulty transposing, reshaping, flipping (not sure which) a data frame which is read from a DBF file. I have tried using t(), reshape() and other approaches without success. Can anyone please suggest an way (elegant or not) of flipping this data around ? The initial data is like propsum (defined below), and I want it to look like tpropsum once reformed. >