similar to: Matrix mulitplication

x <- read.table("LittleGarvin.csv", sep=",", header=TRUE) y <- t(x) str(y) chr [1:193, 1:288] "oligocha" "0" " 0" " 0" " 0" "0" ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:193] "X" "upwd1201" "upwd0502" "upwd0702" ... ..$ : NULL x is a data frame with

Hi I have a square matrix Ainv of size N-by-N where N ~ 1000 I have a rectangular matrix H of size N by n where n ~ 4. I have a vector d of length N. I need X = solve(t(H) %*% Ainv %*% H) %*% t(H) %*% Ainv %*% d and H %*% X. It is possible to rewrite X in the recommended crossprod way: X <- solve(quad.form(Ainv, H), crossprod(crossprod(Ainv, H), d)) where quad.form() is a little

Hi the manpage says that crossprod(x,y) is formally equivalent to, but faster than, the call 't(x) %*% y'. I have a vector 'a' and a matrix 'A', and need to evaluate 't(a) %*% A %*% a' many many times, and performance is becoming crucial. With f1 <- function(a,X){ ignore <- t(a) %*% X %*% a } f2 <- function(a,X){ ignore <-

Hi guys, I need your help. I would like to select a subset from a dataset. This is the dimension of the dataset. > dim(data1) [1] 72 36 1916 so, it's like.. there are 1916 of 72 * 36 matrix. ==> looks like 72 * ( 36*1916 ) ** *1)* And I would like to select the first 72*36 matrix. This is how I did: > two=data1[,1:36] Error in data1[, 1:36] : incorrect number of dimensions

Hello, A collegue of mine has compared the runtime of a linear model + anova in SAS and S+. He got the same results, but SAS took a bit more than a minute whereas S+ took 17 minutes. I've tried it in R (1.9.0) and it took 15 min. Neither machine run out of memory, and I assume that all machines have similar hardware, but the S+ and SAS machines are on windows whereas the R machine is Redhat

Hello everybody When one is working with complex matrices, "transpose" very nearly always means *Hermitian* transpose, that is, A[i,j] <- Conj(A[j,i]). One often writes A^* for the Hermitian transpose. I have only once seen a "real-life" case where transposition does not occur simultaneously with complex conjugation. And I'm not 100% sure that that wasn't a

The solve function in r-patched has been changed so that it applies a tolerance when using Lapack routines to calculate the inverse of a matrix or to solve a system of linear equations. A tolerance has always been used with the Linpack routines but not with the Lapack routines in versions 1.7.x and 1.8.0. (You can use the optional argument tol = 0 to override this check for computational

Hi I need to compare the performance of two sludge inertization methods. For that i want make a manova Wilks test. Description of the experiment: After the calcination at different temperatures my calcinated sludge are submeted to the lixiviation test. In my tables i show the concentration of the some elements in the extract phase. The results: Method A (calcination at 1100 C) Chromium

So, I am having a tricky reference file to extract information from. The format of the file is x 1 + 4 * 3 + 5 + 6 + 11 * 0.5 So, the elements that are not being multiplied (1, 5 and 6) and the elements before the multiplication sign (4 and 11) means actually the reference for the row in a matrix where I need to extract the element from. The numbers after the multiplication sign are regular

Full_Name: Yves Rosseel Version: 2.2.1 OS: i686-pc-linux-gnu Submission from: (NULL) (157.193.116.152) Dear developers, For the single-model case, the anova.mlm() function does not seem to handle multi-parameter predictors (eg factors) correctly. A toy example illustrates the problem: Y <- cbind(rnorm(100),rnorm(100),rnorm(100)) A <- factor(rep(c(1,2,3,4), each=25)) fit <- lm(Y ~ A)

I have an array with 44800 columns and 24 rows I would like to compute the row average for the array 100 columns at a time, so I would like to end up with an array of 24 rows x 448 columns. I have tried using apply(dataset, 1, function(x) mean(x[])), but I am not sure how to get it to take the average 100 columns at a time. Any ideas would be welcomed. thanks, Spencer [[alternative HTML

The following is at least as much out of intellectual curiosity as for practical reasons. On reviewing some code written by novices to R, I came across: crossprod(x, y)[1,1] I thought, "That isn't a very S way of saying that, I wonder what the penalty is for using 'crossprod'." To my surprise the penalty was substantially negative. Handily the client had S-PLUS as

hi, the help page for crossprod states that crossprod(A,B) is faster than t(A) %*% B; experimentation certainly bears this out. more alarming is the evidence that crossprod(t(A), B) is faster than A %*% B: on a PII laptop, 128MB memory, win98, R-1.5.0.-patched precompiled (no ATLAS): > A <- matrix(rnorm(250000),500,500) > B <- matrix(rnorm(250000),500,500) > for (i in 1:5) {

Dear All, I have a problem that I think could be solved much more efficiently, but I don't have a clue how to accomplish this. I have a matrix W with dimensions k*(p+1): Let's say W is 5*4 and looks like this: > W [,1] [,2] [,3] [,4] [1,] 1 -1 -1 1 [2,] 1 1 1 1 [3,] 1 2 -2 -1 [4,] 1 0 -1 -1 [5,] 1 -2 -1 0 I want to take

Hi, For those who are interested, I have update my R benchmark (to version 1.5.0) and also to Splus 6. They are available at: http://www.sciviews.org/other/benchmark.htm. A comparison is made between Matlab (5.3 & 6), R 1.5.0, Splus 6 rel 2, O-Matrix 5.1, Octave 2.1.31, Scilab 2.6, Rlab 2.1 and OX 3.00 under Windows 2000 pro. Overall, R is not the fastest package, but it is one of the

Dear R-Users, Suppose I have data in the following format: CODE_NAME ZIP_CODE John 12345 John 23456 John 34567 Jane 13242 Jane 22123 I want to transpose / convert it into: CODE_NAME ZIP_CODE John 12345,23456,34567 Jane 13242,22123 Any idea/pointer is appreciated.

> From: Douglas Bates [mailto:bates at bates4.stat.wisc.edu] > > "Liaw, Andy" <andy_liaw at merck.com> writes: > > > Sorry. I need to retract my claim. There seems to be a 3G > limit, even > > though the OS could handle nearly 8G. (I can have two > simultaneous R > > processes each using near 3G.) > > > > On another note, on

> From: Douglas Bates [mailto:bates at bates4.stat.wisc.edu] > > "Liaw, Andy" <andy_liaw at merck.com> writes: > > > Sorry. I need to retract my claim. There seems to be a 3G > limit, even > > though the OS could handle nearly 8G. (I can have two > simultaneous R > > processes each using near 3G.) > > > > On another note, on

When I bought two Polycom 501 SIP phones, I naively thought they were Power-over-Ethernet (IEEE 802.3af) because they were "powered over ethernet." Silly me. Polycom must have some odd voltage or funny way of injecting the power, because the POE switch I bought for them (Netgear F@510P) won't power them, though if I use the Polycom-supplied AC adapter and ethernet power

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