similar to: Table to matrix

Dear R users, I have a question about matrix manipulation with its rows. Plz see the simple example below sample <- list(matrix(1:6, nr=2,nc=3), matrix(7:12, nr=2,nc=3), matrix(13:18,nr=2,nc=3)) > sample [[1]] [,1] [,2] [,3] [1,] 1 3 5 [2,] 2 4 6 [[2]] [,1] [,2] [,3] [1,] 7 9 11 [2,] 8 10 12 [[3]] [,1] [,2] [,3] [1,] 13 15 17 [2,]

Dear R users, I'd like to create a block diagonal matrix with each rows in a matrix. Here is a simple example. (In fact, the matrix is big) x <- matrix(1:20, 4,5) > x [,1] [,2] [,3] [,4] [,5] [1,] 1 5 9 13 17 [2,] 2 6 10 14 18 [3,] 3 7 11 15 19 [4,] 4 8 12 16 20 With each rows in matrix x, I'd like to make the matrix below.

Dear R users, I am looking for more efficient way to compute the followings -------------------------------------------------------------------------- a <- matrix(c(1,1,1,1,2,2,2,2),4,2) b <- matrix(c(1,2,3,4),4,1) Eventually, I want to get this matrix, `c`. c <- matrix(c(1/1,1/2,1/3,1/4,2/1,2/2,2/3,2/4),4,2) --------------------------------------------------------------------------

Dear R users... I'd like to change this character vector, "zz", zz <- c("12","56","89") to the following numeric matrix. [,1] [,2] [1,] 1 2 [2,] 5 6 [3,] 8 9 Actually, "zz" vector has a long length. Any comments will be greatly appreciated. Kathryn Lord -- View this message in context:

Dear R users, I'd like to make this data rem.y = c(-1,0,2,4,5) from y = c(-1,-1,0,2,2,2,2,4,4,5,5,5,5,5). That is, I need to remove repeated values. Here is my code, but I don't think it is efficient. How could I improve this? #------------------------------------------------------------------------ y = c(-1,-1,0,2,2,2,2,4,4,5,5,5,5,5) n=length(y) for (i in 1:n) #

Dear R users I'd like to generate two sets of random numbers with a fixed correlation coefficient, say .4, using R. Any suggestion will be greatly appreciated. Regards, Kathryn Lord -- View this message in context: http://r.789695.n4.nabble.com/generate-two-sets-of-random-numbers-that-are-correlated-tp3735695p3735695.html Sent from the R help mailing list archive at Nabble.com.

Dear R users... I need to split this matrix(or dataframe), for example, z <- matrix(c(13,1,1,1,1,12,0,0,0,0,8,1,0,1,1,8,0,1,0,0, 10,1,1,1,1,3,0,1,0,0,3,1,0,1,1,6,1,1,1,1),8,5,byrow = T) > z [,1] [,2] [,3] [,4] [,5] [1,] 13 1 1 1 1 [2,] 12 0 0 0 0 [3,] 8 1 0 1 1 [4,] 9 0 1 0 0 [5,] 10 1 1 1 1

Dear R users... I made this by help of one of R users. _________________________________________________________________ X=matrix(seq(1,4), 2 , 2) B=matrix(c(0.6,1.0,2.5,1.5) , 2 , 2) func <- function(i,y0,j) { y0*exp(X[i,]%*%B[,j]) } list1 <- expand.grid( i=c(1,2) , y0=c(1,2) , j=c(1,2) ) results <- do.call( func , list1 )

Dear R users, I have the list as follows; #------------------------------------------------------ > z [[1]] [[1]][[1]] matrix(A) [[1]][[2]] matrix(B) [[1]][[3]] matrix(C) [[2]] [[2]][[1]] matrix(D) [[2]][[2]] matrix(E) [[2]][[3]] matrix(F) #--------------------------------------------- I'd like to compute matrix(A)+matrix(B)+matrix(C)+matrix(D)+matrix(E)+matrix(F) In

Dear R users, is there way to ignore an error and go back to 1st line? I mean, #------------------------------- while (or repeat) ------------ { 1 2 . . . 6 } #----------------------------- For example, if I have an error in the 6th line, then I'd like to go back to the 1st line. I've already tried "try", but it didn't work. Any suggestion will be greatly

Hi, R users, Here is an example. k <- c(1,2,3,4,5) i <- c(0,1,3,2,1) if k=1, then i=0 if k=2, then i=0, 1 if k=3, then i=0, 1, 2, 3 if k=4, then i=0, 1, 2 if k=5, then i=0, 1 so i'd like to create a list like below. > list k i 1 1 0 2 2 0 3 2 1 4 3 0 5 3 1 6 3 2 7 3 3 8 4 0 9 4 1 10 4 2 11 5 0 12 5 1 I tried expand.grid, but I can't. Any suggestion will be

Dear R users... I made the R-code for this double summation computation http://www.nabble.com/file/p19213599/doublesum.jpg ------------------------------------------------- Here is my code.. sum(sapply(1:m, function(k){sum(sapply(1:m, function(j){x[k]*x[j]*dnorm((mu[j]+mu[k])/sqrt(sig[k]+sig[j]))/sqrt(sig[k]+sig[j])}))})) ------------------------------------------------- In fact, this is

Dear R users, I have two n*1 integer vectors, y1 and y2, where n is very very large. I'd like to compute elbp = 4^(y1) * 5^(y2) * sum_{i=0}^{max(y1, y2)} [{ (y1-i)! * (i)! * (y2-i)! }^(-1)]; that is, I need to compute "elbp" for each (y1, y2) pair. So I made R code like below, but I don't think it's efficient Would you plz tell me how to avoid this "for"

Dear R users When I use OPTIM with BFGS, I've got a significant result without an error message. However, when I use OPTIMX with BFGS( or spg), I've got the following an error message. ---------------------------------------------------------------------------------------------------- > optimx(par=theta0, fn=obj.fy, gr=gr.fy, method="BFGS", >

Dear R users, I try to compute this summation, http://www.nabble.com/file/p25054272/dd.jpg where f(y|x) = Negative Binomial(y, mu=exp(x' beta), size=1/alp) http://www.nabble.com/file/p25054272/aa.jpg http://www.nabble.com/file/p25054272/cc.jpg In fact, I tried to use "do.call" function to compute each u(y,x) before the summation, but I got an error, "Error in X[i, ]

Dear list; I just created a utility function that replicates what I have done in the past with Excel or OO.org by putting a formula of the form =sum($A1:A$1) in an upper-corner of a section and then doing a "fill" procedure by dragging the lower-rt corner down and to the right. When divided by the grand sum of the entries this function then calculates a 2D-discrete-ECDF. I

Dear R users I am trying to use OPTIMX(OPTIM) for nonlinear optimization. There is no error in my code but the results are so weird (see below). When I ran via OPTIM, the results are that Initial values are that theta0 = 0.6 1.6 0.6 1.6 0.7. (In fact true vales are 0.5,1.0,0.8,1.2, 0.6.) -------------------------------------------------------------------------------------------- >

Buenos días: Después de más de 20 años en SAS, ahora igual me toca trabajar en R. Y la transición es muy dura: la "lógica" de los dos lenguajes es, para mi, totalmente diferente. Disculpen si lo que pregunto es una obviedad, pero llevo todo el día con esto y no logro encontrar la respuesta adecuada con google. Estoy intentado crear una función que realice una descriptiva simple de

Dear all, I'm having a few problems trying to reshape a data frame. I tried with reshape{stats} and melt{reshape} but I was missing something. Any help is very welcome. Please find details below: ################################# # data in its original shape: indiv <- rep(c("A","B"),c(10,10)) level.1 <- rpois(20, lambda=3) covar.1 <- rlnorm(20, 3, 1) level.2

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