similar to: Memory Efficient Methods for Building Matrix

Dear List: I am working to construct a matrix of a particular form. For the most part, developing the matrix is simple and is built as follows: vl.mat<-matrix(c(0,0,0,0,0,64,0,0,0,0,64,0,0,0,0,64),nc=4) Now to expand this matrix to be block-diagonal, I do the following: sample.size <- 100 # number of individual students I<- diag(sample.size) bd.mat<-kronecker(I,vl.mat) This

Dear List: I am having some difficulty constructing a matrix that must take a specific form. The matrix must be have a lower block of non-zero values and the rest must all be zero. For example, if I am building an n X n matrix, then the first n/2 rows need to be zero and the first n/2 columns must remain as zero with all other elements having a non-zero value that I specify. For example, assume

Dear List: I'm working to construct a very large sparse matrix and have found relief using the SparseM package. I have encountered an issue that is confusing to me and wonder if anyone may be able to suggest a smarter solution. The matrix I'm creating is a covariance matrix for a larger research problem that is subsequently used in a simulation. Below is the latex form of the matrix if

Dear R users, Suppose i have an A square matrix rxr. I want to obtain a block matrix B (pxr,pxr) where the p diagonal blocks are A and the others values are 0. I would like to do something like : diag(A,ncol=pr, nrow=pr) How can i do it ?? Thanks in advance, Olivier. -- -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- Olivier MARTIN PhD student phone: (33) 04

Hi All, I'm a little stumped by the following problem. I've got a dataset with the following structure: idxy ix iy country (other variables) 1 1 1 c1 x1 2 1 2 c1 x2 3 1 3 c1 x3 . . . . . 3739 55 67 c7 x3739 3740 55 68 c7 x3740 where ix and

Hey all Im having a problem... Ok, this is the situation... I have a small product image, on which ive floated a div over it, and defined it as draggable. Now, this works, and i can drag it around no problem. great. but then, what i want to do is, based on the location of that dragable element from the top and the left, to move (using the Effect.MoveBy method) a larger image - so effective

Dear List: I have a question regarding an MDS procedure that I am accustomed to using. I have searched around the archives a bit and the help doc and still need a little assistance. The package isoMDS is what I need to perform the non-metric scaling, but I am working with similarity matrices, not dissimilarities. The question may end up being resolved simply. Here is a bit of substantive

Dear List: A few weeks ago I posted some questions regarding data simulation and received some very helpful comments, thank you. I have modified my code accordingly and have made some progress. However, I now am facing a new challenge along similar lines. I am attempting to simulate 250 datasets and then run the data through a linear model. I use rm() and gc() as I move along to clean up the

For a Z80 backend, "eliminateCallFramePseudoInstr()" shall adjust the stack pointer in three possible ways, e.g. after a function call, depending on the amount (= adjustment size) *and some other rules*: 1. via one or more target "pop <reg>" instructions (SP increments +2 per instruction), using an unused reg (disregarding the contents after the operation), followed

Dear all; Does anyone know how to add grid lines to a persp plot? I've tried using lines(trans3d..) but the lines of course are superimposed into the actual 3d surface and what I need is something like the plot shown in the following link: http://thermal.gg.utah.edu/tutorials/matlab/matlab_tutorial.html I'll appreciate any ideas Thanks PM

Dear List: First, many thanks to those who offered assistance while I constructed code for the simulation. I think I now have code that resolves most of the issues I encountered with memory. While the code works perfectly for smallish datasets with small sample sizes, it arouses a windows-based error with samples of 5,000 and 250 datasets. The error is a dialogue box with the following: "R

Yes, such optimizations are something for the "last 20%" of the project, nice to have's. As of now, I have yet to get a feeling of what LLVM can do on its own, depending on what it's from the instruction tables and where it needs help, and how much in other processing stages. As this affects the way how the instruction info table will be set-up, I appreciate your suggestions

The ivdep pragma is designed to do exactly what the name states - ignore vector dependencies.  Cray Research first implemented this in 1978 in their CFT compiler, and has supported it since. This pragma is typically used by application developers who want vectorized code when the compiler cannot automatically determine safety; it is not equivalent to the OpenMP SIMD pragma in that the compiler is

Hi I have some panel data for the 50 US states over about 25 years, and I would like to test a simple model via OLS, using this data. I know how to run OLS in R, and I think I can see how to create Panel Corrected Standard Errors using http://jackman.stanford.edu/classes/350C/pcse.r What I can't figure out is how to correct for autocorrelation over time. I have found a lot of R stuff on

Dear R-users, I would like to know whether there is a way to extract a diagonal of an inverse matrix without computing the inverse of the matrix itself. The size of my matrices are really huge and, also using sparse matrix, computing the inverse leads to storage problems and low speed. In other words, given a square matrix A, I aim to know diag(B), where B=solve(A), without computing solve(A).

This is a question about optimizing the code generation in a (new) Z80 backend: The CPU has a couple of 8 bit physical registers, e.g. H, L, D and E, which are overlaid in 16 bit register pairs named HL and DE. It has also a native instruction to load a 16 bit immediate value into a 16 bit register pair (HL or DE), e.g.: LD HL,<imm16> Now when having a sequence of loading two 16

Dear List: I am running into a memory issue that I haven't noticed before. I am running a simulation with all of the code used below. I have increased my memory to 712mb and have a total of 1 gb on my machine. What appears to be happening is I run a simulation where I create 1,000 datasets with a sample size of 100. I then run each dataset through a gls and obtain some estimates. This works

I have a question about antialiasing when R generates bitmaps. (This follows a thread on the ggplot2 mailing list.) I mostly use R on Linux, although I sometimes use it in Mac and Windows as well. On Linux, I've found that plotting shapes 15-18 via cairo results in bad-looking output. The points are not antialiased, and they are jagged and misshapen. Plots generated in Windows also aren't

I've found the need to compute a version of order(x,y) where I want the sort order for *increasing* x and *decresing* y ... something we could imagine could be provided in the future as order(x,y, decreasing = c(FALSE, TRUE)) i.e., using a 'vectorized' decreasing argument. {No, I'm not volunteering right now!} I've found the following R-level solution and like to quiz

Dear all, I just installed the new version of R, 2.10.1, and I am currently using the package sparseM. (I also use a 64 bit windows version) I got a problem that I never had: when I try to multiply with a kronecker product (%x%) two sparse matrixes I get the following message: Error in dim(x) <- length(x) : invalid first argument I never had this problem with previous versions of R. May