similar to: How to 'explode' a matrix

Two posts in one day is not a good day...and this question seems like it should have an obvious answer: I have a matrix where rows are unique combinations of 1's and 0's: > combs=as.matrix(expand.grid(c(0,1),c(0,1))) > combs Var1 Var2 [1,] 0 0 [2,] 1 0 [3,] 0 1 [4,] 1 1 I want a single function that will give the row index containing an exact match

Hi everyone, Speed is the key here. I need to find the difference between a vector and its one-period lag (i.e. the difference between each value and the subsequent one in the vector). Let's say the vector contains 10 million random integers between 0 and 1,000. The solution vector will have 9,999,999 values, since their is no lag for the 1st observation. In R we have: #Set up input vector

Take vector x and a subset y: x=1:10 y=c(4,5,7,9) For each value in 'x', I want to know how many elements in 'y' are less than 'x'. An example would be: sapply(x,FUN=function(i) {length(which(y<i))}) [1] 0 0 0 0 1 2 2 3 3 4 But this solution is far too slow when x and y have lengths in the millions. I'm certain an elegant (and computationally efficient)

Hi I want to write a little function that takes a matrix X of size m-by-n, and a list L of length "m", whose elements are matrices all of which have the same number of columns but possibly a different number of rows. I then want to get a sort of dumbed-down kronecker product in which X[i,j] is replaced by X[i,j]*L[[j]] where L[[j]] is the j-th of the "m" matrices. For

Dear All, Could someone please suggest how to find the Kronecker sum of two 2x2 matrices, i.e. given two matrices: -A A a -a and -B B b -b I need: -A-B A B 0 a -a-B 0 B b 0 -A-b A 0 b a -a-b Many thanks, Lara [[alternative HTML version deleted]]

Anyone know what the Ruby equivalent of PHP''s explode and implode are for arrays? - Jim

How can I create the following without the 'for' loop? start=c(1,10,20) end=c(4,15,27) out=c() for (i in 1:length(start)) { out=c(out,start[i]:end[i]) } out [1] 1 2 3 4 10 11 12 13 14 15 20 21 22 23 24 25 26 27 I know there must be an easier (and, hopefully, faster) way. Many thanks in advance, Kevin Ummel Central European University Department of Environmental Science and

For an application, I have formulas defined in terms of a left Kronecker product of matrices, A,B, meaning A \otimes_L B = {A * B[i,j]} -- matrix on the left multiplies each element on the right. The standard kronecker() function is the right Kronecker product, A \otimes_R B = {A[i,j] * B} -- matrix on the right multiplies each element on the left. The example below shows the result of

Hi I'm using kronecker() with a matrix and a vector. I'm interested in the column names that kronecker() returns: > a <- matrix(1:9,3,3) > rownames(a) <- letters[1:3] > colnames(a) <- LETTERS[1:3] > b <- c(x=1,y=2) > kronecker(a,b,make.dimnames=TRUE) A: B: C: a:x 1 4 7 a:y 2 8 14 b:x 2 5 8 b:y 4 10 16 c:x 3 6 9 c:y 6 12 18 > The

I'm trying to calculate the row-wise kronecker product A \Box B of two sparse matrices A and B, and am struggling to find a quick way to do this that takes advantage of sparseness. I thought a good idea would be to use "rep" to construct 2 matrices of the same dimension of the end product, and multiply these two together: library(Matrix) A<-Matrix(c(1,0,0,0,0,1,2,0), 2, 4)

A bit embarrassed to post this seemingly trivial question, but I can't find anything in the archive that's quite relevant: a1=1 a2=2 obs=objects(pattern=glob2rx("a?")) I want to utilize 'obs' as a function argument to produce something like: sum(a1,a2) Obviously, sum(obs) doesn't work, but I've tried variations of 'eval', 'parse',

Hi to all, i''m using htb.init for configuring my shaper. Now i want to know if it possible to show how htb.init make and use TC, anyone has tried it? Many thanks. -- Stefano Mainardi Presidente Associazione ILDN - Italian Linux Distro Network Mobile: 349/3917212 Skype: mainardistefano IM (ICQ): 250-292-408 Blog: http://www.mainardistefano.org

kronecker, with make.dimnames=TRUE uses a hardwired sep=":" in the line tmp <- outer(dnx[[i]], dny[[i]], FUN = "paste", sep = ":") For an application in which dimnames arise from an n-way array, where different dimensions have different roles, and I would like to be able to use kronecker in the form kronecker(A, B, make.dimnames=TRUE,

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]

Hello all, A colleague at work set me the challenge to convert some MATLAB code into R, to see which is faster. We'd seen that benchmark comparing MATLAB 6.5 to R1.90 (and others), and so I thought that I should be able to get roughly comparable speeds. The code has lots of multiplications of matrixes, transposes, and MATLAB's "repmat". I did the code conversion, and R was about

Hi, I'm trying to compute  the spatiotemporal correlation matrix by using Delta Kronecker products of spatial and temporal correlation matrix  in R, but didn't find any delta Kronecker's operator in R. The operators in matrix such as multiplication, addition, eigen values/vector and etc is easily to find and used. Could someone help me, please? Cheers. Firdaus

Hi R users all , I have a clean install of R-2.15.0 in a win32 machine and a problem loading Matrix 1.0-6 that looks like this: > library(Matrix) Loading required package: lattice Error : object ?kronecker? is not exported by 'namespace:methods' Error: package/namespace load failed for ?Matrix? > I understand that kronecker() now has an S4 generic in package methods. Is that a

I'm translating some Matlab code and need some help figuring out how to change this call into an S4 generic method. In matlab, there's a function called 'repmat' with three calling sequences (all I have to deal with anyway): 1) B = repmat(A, m, n) 2) B = repmat(A, [m n]) 3) B = repmat(A, n) In all cases, A is the fill value, m is number of rows, and n is number of

Dear expeRts, I have two matrices A and B. They have the same number of columns but possibly different number of rows. I would like to compare each row of A with each row of B and check whether all entries in a row of A are less than or equal to all entries in a row of B. Here is a minimal working example: A <- rbind(matrix(1:4, ncol=2, byrow=TRUE), c(6, 2)) # (3, 2) matrix B <-

Dear R-users, I coded two equivalent ways to perform (in a simplified version) some matrix multiplications I would like to use in a more general framework. In the first case I used Kronecker product and vectorization of a certain matrix. This approach takes less time, but, as you may guess, I run out of memory when dimensions are large. In the second approach, I profited of sparseness and