similar to: trade-off between speed and storage in matrix multiplications

Dear list members, Any help on this efficiency issue would be greatly appreciated. I would like to find the most efficient way to run a non-vectorized function (here: fisher exact test p-value) iteratively using 4 matrices with identical dimensions. And as a result I aim for an array with identical dimensions containing the corresponding p-values. Please consider some code using a trivial

Dear R users, I'm wanting to sample from the negative binomial distribution using the rnegbin function from the MASS library to create artificial samples for the purpose of doing some power calculations. However, I would like to work with samples that come from a negative binomial distribution that includes only values greater than or equal to 1 (a truncated negative binomial), and I

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

ices.conf: <Public>1</Public> <!-- The name of you stream, not the name of the song! --> <Name>Poohba's Urban Sounds</Name> <!-- Genre of your stream, be it rock or pop or whatever --> <Genre>RnB</Genre> icecast.xml <directory> <yp-url-timeout>15</yp-url-timeout>

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

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,

Jack Moffitt <jack@xiph.org> writes: > Now I see the problem. This will not cause anything to show up. You > have no sources. Eh? -> sources Listing sources [Id: 509] [Sock: 14] [Time of connect: 18/Feb/2002:20:55:14] [IP: 205.147.43.110] [State: 1] [Type: pulling relay] [Proto: x-audiocast] [Clients: 2] [Dumpfile/fd: (null)/-1] [Priority: 0] [Song Title: ] [Song URL:

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)

I thought the YP code was going to be fixed to use less resources so it could be used with other stream formats. It seems to be taking a long time. As it is now, Icecast2 is not a good solution for those wanting to be on a popular directory. I am forced to recommend using Shoutcast to my clients so they can get onto a popular directory. I would prefer to recommend Icecast2. Ross Levis.

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

notice: /subject.sol1.net/virtual_mail_server/File[/etc/postfix]/checksum: checksum changed ''{time}Thu Jan 25 16:31:08 EST 2007'' to ''{time}Thu Jan 25 16:36:39 EST 2007'' I know there''s something weird in the directory modification detection that causes the next run after things actually change to suffer from this problem, but I''m getting it

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

Just noticed that I get a similar error about object 'kronecker' in "Matrix" package when trying to load "lme4". So this is a more pervasive problem. Brian Brian S. Cade, PhD U. S. Geological Survey Fort Collins Science Center 2150 Centre Ave., Bldg. C Fort Collins, CO 80526-8818 email: brian_cade@usgs.gov tel: 970 226-9326 ----- Forwarded by Brian S

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]]

I recently lost the partitions on my hard drive (second time in 6 months) so I had to have our IT folks image all my files over to a new drive. I completely reinstalled R (now 2.15.2) and all my libraries to my computer (Dell Latitude running Windows 7). A few of my previous workspaces (created with R 2.14.1) can't be restored, reporting an error similar to the one I get when I try to

Dear helpers, I wrote a code which estimates a multi-equation model with generalized least squares (GLS). I can use GLS because I know the covariance matrix of the residuals a priori. However, it is a bit slow and I wonder if anybody would be able to point out a way to make it faster (it is part of a bigger code and needs to run several times). Any suggestion would be greatly appreciated. Carlo

`outer` (and related functions like kronecker) require that their functional argument operate elementwise on arrays. This means for example that outer( 1:2, 3:4, list) or outer(1:2,3:4,function(a,b){1}) gives an error. Is there a version of `outer`/`kronecker`/etc. that takes arbitrary functions and does its own elementwise mapping? In the first example above, I'd expect the

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

I can understand wanting to boost the adoption of Xiph codecs, but I think restricting the directory to vorbis streams only will not help this endeavour. I can imagine it will just piss a lot of people, including myself, and give Xiph a bad name. I get very few listeners of my AAC+ stream now since this occured. The restriction is not an insentive to switch to Ogg Vorbis at all. The incentive