similar to: Using a Data Frame/Matrix outside a function

Suppose I have a square matrix P P <- matrix(c(.3,.7, .7, .3), ncol=2) I know that > P * P Returns the element by element product, whereas > P%*%P Returns the matrix product. Now, P^2 also returns the element by element product. But, is there a slick way to write P %*% P %*% P Obviously, P^3 does not return the result I expect. Thanks, Harold [[alternative HTML version

Hello, I am trying to build a large size identity matrix using diag(). The size is around 23000 and I've tried diag(23000), that took a long time. Since I have to use this operation several times in my program, the running time is too long to be tolerable. Are there any alternative for diag(N)? Thanks Cheers, yct [[alternative HTML version deleted]]

dear R experts: ?I am writing my own little newey-west standard error function, with heteroskedasticity and arbitrary x period autocorrelation corrections. ?including my function in this post here may help others searching for something similar. it is working quite well, except on occasion, it complains that Error in solve.default(crossprod(x.na.omitted, x.na.omitted)) : system is

Hi, I have worked long and hard and looked in the manuals and am having a hard time constructing a diagonal matrix. I can get the diagonals out of a matrix but can't construct the matrix with just the diagonals. I have been on the web site and manuals and I think that it says to use: dsj <- diag (three = 1, nrow, ncol = 7) three is the name of my matrix and

thank you, achim. I will try chol2inv. sandwich is a very nice package, but let me make some short suggestions. I am not a good econometrician, so I do not know what prewhitening is, and the vignette did not explain it. "?coeftest" did not work after I loaded the library. automatic bandwidth selection can be a good thing, but is not always. as to my own little function, I like the

Dear R list, I have the following data: set.seed(1) n <- 5 # number of subjects tt <- 3 # number of repeated observation per subject numco <- 2 # number of covariates x <- matrix(round(rnorm(n*numco),2), ncol=numco) # the actual covariates x > x [,1] [,2] [1,] -0.63 -0.82 [2,] 0.18 0.49 [3,] -0.84 0.74 [4,] 1.60 0.58 [5,] 0.33 -0.31 I need to form a matrix

Hello, I would like to take advantage of the upper.tri() function here but I don't know exactly. Here is some working code... i<-5 fi<-matrix(0,nrow=i,ncol=i) for(r in 1:i){ for(c in 1:i){ if(r==c){ fi[r,c]<-1 }else if(r<c){ fi[r,c]<-1-runif(1)^.5 }else{ fi[r,c]<-fi[c,r] } } } So far I know I can simplify this code to 5 lines (no for loops): i<-5

Dear List: I am having to build a block-diagonal matrix (vl) and am currently using the following code. I<-diag(sample.size) vl<-kronecker(I,vl.mat) This code works fine, but for large N, it is a huge memory hog. Is there a more efficient method for constructing vl? Thanks, Harold [[alternative HTML version deleted]]

Hi, Does anybody know, what is going on here? > diag(sqrt(1)) [,1] [1,] 1 > diag(sqrt(0.3333)) <0 x 0 matrix> > sqrt(1) [1] 1 > sqrt(0.3333) [1] 0.5773214 BR, Markku Karhunen researcher University of Helsinki

Dear all, Currently I am trying to integrate a function which depends on four variables, two of which are given, one is given in the integrate function, so there is one variable to integrate on. The code is as follows: Pmatrix = function(th) { P = matrix(nrow=6, ncol=6, data=0) P[1,1] = P[2,1]=P[3,2]=P[4,3]=P[5,4]=P[6,5]= exp(-th) P[,6] = 1-exp(-th) return(P)} lim.verd =

I'm still having difficulties with methods...is the following behavior expected? (This is without loading any libraries) R : Copyright 2003, The R Development Core Team Version 1.7.0 Under development (unstable) (2003-03-31) > ls() character(0) > > diag(2) [,1] [,2] [1,] 1 0 [2,] 0 1 > setGeneric("diag") [1] "diag" > diag(2) Error in

Using diag() to extract the diagonal of a matrix loses all but the first dimname (R 0.62.3). The problem seems to be in [ ]: > > x <- matrix(1:9,3,3) > dimnames(x) <- list(c("a", "b", "c"), c("a", "b", "c")) > x a b c a 1 4 7 b 2 5 8 c 3 6 9 > diag(x) a NA NA 1 5 9 > x[c(1,5,9)] a NA NA 1 5 9 > Paul

Hello, Using the dse package I have estimated a VAR model using estVARXls(). I can perform forecasts using forecast() with no problems, but when I try to use simulate() with the same model, I get the following error: Error in diag(Cov, p) : 'nrow' or 'ncol' cannot be specified when 'x' is a matrix Can anyone shed some light on the meaning of this error? How can I

Dear useRs, i have certain commands for some operations in R. They are good if you have a small dataset but my dataset, apart from what i used in the recent past, is prety large. I want to convert these massive sets of commands into a simple loop. Your help is required on it thanks in advance eliza kindly note: "e" is matrix whose each column has to be executed into a distance vector

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I have two matrices: > m1 <- matrix(1,4,4) > m1 [,1] [,2] [,3] [,4] [1,] 1 1 1 1 [2,] 1 1 1 1 [3,] 1 1 1 1 [4,] 1 1 1 1 > m2 <- matrix(0,3,3) > diag(m2) <- 1 > m2 [,1] [,2] [,3] [1,] 1 0 0 [2,] 0 1 0 [3,] 0 0 1 I want to get indicies from m2

Hi, May be this helps: ?tb[1,]%*%(((val-rep(meansb79[1,],5))^2)/6) #??????? [,1] #[1,] 1.47619 tryvarb<-c(1,2,3,4,4,4,4) ?var(tryvarb) #[1] 1.47619 tb[2,]%*%(((val-rep(meansb79[2,],5))^2)/6) #???????? [,1] #[1,] 1.904762 sapply(seq_len(nrow(tb)),function(i) tb[i,]%*%(((val-rep(meansb79[i,],5))^2/6))) # [1] 1.4761905 1.9047619 1.9047619 1.9047619 1.9047619 2.2857143 1.9047619 # [8] 1.9047619

I have just put up a new executable as a replacement for the one in rseptbeta.zip there have only been a few changes; mostly to the menu's. I am about to start on a major overhaul including getting survival to work and grabbing the 0.60 version once it's stable. Please let me know about other enhancements you want.... robert

I have just put up a new executable as a replacement for the one in rseptbeta.zip there have only been a few changes; mostly to the menu's. I am about to start on a major overhaul including getting survival to work and grabbing the 0.60 version once it's stable. Please let me know about other enhancements you want.... robert

Hi, suppose that we have a triangular upper matrix A test <- matrix(ncol = 4, nrow = 4) test[1, ] <- c(NA,1,1,1) test[2, ] <- c(NA,NA,1,1) test[3, ] <- c(NA,NA,NA,1) test[4, ] <- c(NA,NA,NA,NA) I know how quickly set diagonal value diag(test) <- 1. But how quickly set down value i.e. matrix is symmetrical? Is there in r project any quickly function? Thanks, Best Marcin

As kindly pointed out to me (oh my decaying gray matter), is.object() is better suited for this test; $ svn diff src/library/base/R/diag.R Index: src/library/base/R/diag.R =================================================================== --- src/library/base/R/diag.R (revision 68345) +++ src/library/base/R/diag.R (working copy) @@ -23,9 +23,11 @@ stop("'nrow' or