similar to: most efficient plyr solution

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

I am trying to do some research that involves instrumenting LLVM IR, that I need to test for performance and scalability on a bunch of systems. I've started trying by trying to get sparc-sun-solaris2.10 (niagara) working. It appears that neither llvm nor llvm-gcc will build natively on the system, so I think that I need to build an llvm-gcc cross compiler. The documentation for building

The following paper may be of interest to some. The author is generous about sharing a recently revised version. <A HREF="http://papers.ssrn.com/sol3/papers.cfm?abstract_id=259648">http://papers.ssrn.com/sol3/papers.cfm?abstract_id=259648</A> [[alternative HTML version deleted]]

>From a somewhat ill-designed education experiment, I have categorical data with two between subject variables and one within subject variable. Since it is categorical (essentially counts of answer choices on multiple choice questions), I'm looking for some chi-squared method. I know how to generalize Pearson's chi-square for n between subject dimensions, and I know McNemar's test

Hello all, I am trying to install the llvm-gcc front end to use it in one of my projects, but I got stuck.. I am working on a Sun workstation: SunOS xxx 5.10 Generic_137137-09 sun4u sparc SUNW,Sun-Fire-V240 and I have gcc version 3.4.6: Reading specs from /sw/gcc-3.4.6/lib/gcc/sparc-sun-solaris2.10/3.4.6/specs Configured with: /.scratch/andjo/lsw/src/gcc/gcc-3.4.6/configure

Hi all ARCH modelling I have a problem now on how to proceed with further steps in my analysis. I did a linear OLS regression with my daily data of stock and index returns. There is now the problem of arch in my error terms. Thus I used the following r command: garch(resid_desn, order=c(0,2)) ## This ARCH(2) process seems to fit the best after trial and error. Consequently, I get there three

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 have a problem on how to proceed with further steps in my analysis. I did a linear OLS regression (ri,t=alpha*beta*rm,t+et) with my daily data of stock and index returns. There is now the problem of arch in my error terms. Thus I used the following r command: /garch(resid_desn, order=c(0,2)) ## This ARCH(2) process seems to fit the best after trial and error. Consequently, I get there

Dear all, version 1.0-1 of package PMwR is on CRAN now. PMwR stands for 'Portfolio Management with R', and the package provides tools for the practical management of financial portfolios: backtesting investment and trading strategies, computing profit/loss and returns, analysing trades, handling lists of transactions, reporting, and more. The manual [1] provides all the details; a

Dear all, version 1.0-1 of package PMwR is on CRAN now. PMwR stands for 'Portfolio Management with R', and the package provides tools for the practical management of financial portfolios: backtesting investment and trading strategies, computing profit/loss and returns, analysing trades, handling lists of transactions, reporting, and more. The manual [1] provides all the details; a

Luke Dalessandro wrote: > OK. So I've discovered --with-sysroot which seems to be grabbing and > patching the include files correctly. Now it's dieing with > > ./options.h:462: error: 'HOST_BITS_PER_INT' undeclared here (not in a > function) > ./options.h:462: error: bit-field 'padding' width not an integer constant > > which appears to be

The specific standards process used to develop the MPEG codecs creates patent minefields that royalty-free codecs don't generally face. Because many knowledgeable people have heard of the problems faced by these patent-soup standards, they may extrapolate these risk to codecs developed under a different process where these problems are less considerable. This is a mistake, and I'll explain

Hi, I have setup a RAID1 using 3 devices (500G each) on separate disks. After removing one disk physically the filesystem cannot be mounted in degraded nor in recovery mode. When putting the disk back in the filesystem can be mounted without errors. I did a cold-swap (powercycle after removal/insertion of the disk). Here are the details: - latest kernel 3.2.1 and btrfs-tools on xubuntu

Dear R-help forum members, Suppose I have a data-frame having two variables and single data for each of them, as described below. variable_1           variable_2         10                          20 I have written a function, say, 'fun' which uses input 10 and 20 and gives me desired result. fun = function(X, Y)          {          X + Y              #( I am just giving an example of

I am looking for a method of dealing with the modified Bessel function K_\nu(x) for large \nu. The besselK function implementation of this allows for dealing with large values of x by allowing for exponential scaling, but there is no facility for dealing with large \nu. What would work for me would be an lbesselK function in the manner of lgamma which returned the log of K_\nu(x) for large

Dear all, I need to calculate tr(xyxy) fast for matrices x and y. Inspired by the R-source code, I've created the following functions (I am *new* to writing external C-functions, so feel free to laugh at my code - or, perhaps, suggest changes): #include <Rinternals.h> #include <R_ext/Applic.h> /* for dgemm */ static void matprod(double *x, int nrx, int ncx, double *y, int

Not an expert in programming either, but to me it seems like you've forgotten to initialize the variable "tr". It just picks up garbage from allocated memory previously initialized by other processes. Med venlig hilsen Frede Aakmann T?gersen > -----Oprindelig meddelelse----- > Fra: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch] P?

With some chagrin after spending a couple of hours trying to debug a script, I realized I had typed in something like ans<-optimx(start, myfn, mygr, lower<-lo, upper=up) that is, the "<-" rather than "=". The outcome on my machine was a non-obvious error several layers deep in the call stack. For info, optim() seems to stop much more quickly. The error is

Hi. I'm looking for an efficient way of writing a function(x,mat1,mat2). n<-4 m<-4 r<-3 x <- array(sample(1:1000)/10^4,rep.int(n,m)) mat1 <- matrix(sample(1:1000)/10^4,n,n) mat2 <- matrix(sample(1:1000)/10^4,n,n) It needs to work for *any* itegers n, r<=m with output (in horrible gory detail) equivalent to: ans<-array(0,rep.int(n,(m+1))) for(i1 in 1:n) for(i2 in

Dear all, I'm stuck with a problem using plyr to process a rather large junk of data. What I'm trying to do is applying a moving average to all the subparts of the dataframe (the example data can be found here https://dl.dropboxusercontent.com/u/2414056/testData.Rdata). require(plyr) load("testData.Rdata") applyfilter<-function(x){ return(filter(x,rep(1/5, times=5))) }