similar to: an array of matrices

Hi, I'd like to reshape a sparse matrix generated from the Matrix package. I can't seem to do it with the command dim(A) <- c(6,9) which works perfectly with the base package matrices, but with the sparse matrices it errors with Error in dim(A) = c(6, 9) : dim<- : invalid first argument Manipulating the Dim attribute of the sparse Matrix does not produce the desired effect. A

I'd like to perform return variable assignments like matlab. For example, the following function would return A, B, and c to the script that called it. ================================= function [A,B,c] = simple(m,n) A=[ 3 2; 3 3] B=m c=1:n ================================= I'd like to do similar assignments in R, but I seem to be able to only return one variable. I tried to use a

Hi every one, How is it possible to create a matrix with 3 dimensions from several 2 dimensional matrice? Is it possible that each of "elementary/building block" matrices could be called by its corresponding original name? Thanks alot. -- View this message in context:

Dear R-helpers, I have 4-dimensional atmospheric data (x,y,z,t), which I want to analyse on spatio-temporal diversities. As far as I understand there only exists the possibility to construct time series as two-dimensional matrices (mts). For the moment, I hold it in different objects: 1. a four-dimensional array for the spatial related analyses 2. a two-dimensional mts timeserie, which was

Dear all, I think that my question is very simple but I failed to solve it. I have a list which elements are matrices like this: >mylist [[1]] [,1] [,2] [,3] [1,] 1 3 5 [2,] 2 4 6 [[2]] [,1] [,2] [,3] [1,] 7 9 11 [2,] 8 10 12 I'd like to create a matrix M<-mylist[[1]]+mylist[[2]] [,1] [,2] [,3] [1,] 8 12 16 [2,] 10 14 18

Hi I have two arbitrarily dimensioned arrays, "a" and "b", with length(dim(a))==length(dim(b)). I want to form a sort of "corner-to-corner" version of abind(), or a multidimensional version of blockdiag(). In the case of matrices, the function is easy to write and if a=matrix(1,3,4) and b=matrix(2,2,2), then adiag(a,b) would return: [,1] [,2] [,3] [,4] [,5]

Hello All, I have a Linux computer and do all of my work from it. However, I teach also, which means that many of my students use windows. Hence, I need to create packages that work under windows as well as Linux. I have tried to follow the directions at http://cran.r-project.org/doc/contrib/cross-build.pdf which is the document "Building Microsoft Windows Versions of R and R packages

Hello, I have been wondering of an efficient way to do this: I have an n x m x p array Z and a p x n matrix Y. I want to multiply each of the n matrices with the corresponding column vector of Y. In other words, I am wanting to matrix multiply: Z[i, ,] %*% Y[, i] which will give me a (two-dimensional) array or matrix of dimension n x p with the i'th row storing the above. Any pointers

I need to set up Rcmdr for use in a testing center that uses Windows. Since it is in a testing center, we don't want to have data saved, and want it cleared (or never saved) each time R or Rcmdr is run. The method I used to get Rcmdr to run automatically is to add the lines: ------------------------------------------------ defpack = getOption("defaultPackages") mylibs =

I have four large two-dimensional matrices of which I want to create contour plots. Something like filled.contour(<matrix>) contourplot(<matrix>) works but only gives me one plot at a time. If I combine the four matrices into one three-dimensional matrix, which I'll name "seven", there should be a way of doing something like this contourplot(seven[,,k] for k in 1 to 4)

Hello. I have a 4 dimensional array and I want to fill in the slots with values which are a function of the inputs. Through searching the forums here I found that the function "outer" is helpful for 2x2 matrices but cannot be applied to general multidimensional arrays. Is there anything which can achieve, more efficiently than the following code, the job I want? K <-

Hi all, I was unable to find a solution to my problem in the archives, but this might be due to a lack knowledge on the correct terminology on my part. Please forgive me if this has been explained before and please forgive me my probably clumsy way of explaining things. This is what I want to do: I have a list made up of 6 lists containing 7 4x4 matrices each. My goal is to select a large

I have the following array: 3 dimensional object, one dimension being year. Object is 3*3*3 library(plyr, reshape) a1<-rep(c(2007,2008,2009),9) a2<-c(rep("a",9),rep("b",9),rep("c",9)) a3<-c(rep(c(rep(1,3),rep(2,3),rep(3,3)),3)) a4 <- rnorm(27) A<-data.frame(cbind(comp=a2,val=a3, year=a1, a4)) A1<-melt(A, id=c("year", "comp",

Hi I have another question concerning matrices: I have two matrices: > b <- matrix(1:25,5,5,byrow=T) > b [,1] [,2] [,3] [,4] [,5] [1,] 1 2 3 4 5 [2,] 6 7 8 9 10 [3,] 11 12 13 14 15 [4,] 16 17 18 19 20 [5,] 21 22 23 24 25 and > d <- matrix(1:4,2,2,byrow=T) > d [,1] [,2] [1,] 1 2 [2,] 3 4

Dear R user, I'm trying to find a solution for optimizing my code. I have to run a 50.000 iteration long simulation and it is absolutely necessary to have an optimized code. I have to do this operation *sum_t ( t(X_t) %*% A %*% X_t )* where X_t is a (d*k) matrix which changes in time and A is a constant in time (d*d) matrix. I have put all my X_t in a three dimensional array X of dimension

Hi all. I want to calculate partial correlations while controlling for one or more variables. That works already fine when I control for example just for x[,1] and x[,2] that gives me one single correlation matrix and i have to to it for x [,1]...x[,10]. That would give me out 10 matrices. Controlling for 2 Variables 100 matrices. how can I run a loop to get f.e the 10 or 100 matrices at once?

Is there a simple way to calculate summary statistics for all the matrices or dataframes in a list? For example: > z <- list(matrix(c(2,2,2,2), ncol = 2), matrix(c(4,4,4,4), ncol = 2)) > z [[1]] [,1] [,2] [1,] 2 2 [2,] 2 2 [[2]] [,1] [,2] [1,] 4 4 [2,] 4 4 > I would like to calculate, for example, the mean value for each cell. I can do that the hard

Hello all, I have data from a csv that i need to coerce into a multi dimensional array. As you can see from my sample code i have yet to master building efficient code. I can sort of do what i want but its very cumbersome code and i know there is a better way to do it, i am just not expereinced enought yet. So for the following: #Create Data h1i1a1<-sample(1:20, 5, replace=TRUE)

Dear R community, I have a general question regarding indexing in multidiemensional arrays. Imagine I have a three dimensional array and I only want to extract on vector along a single dimension from it: data <- array(rnorm(64),dim=c(4,4,4)) result <- data[1,1,] If I want to extract more than one of these vectors, it would now really help me to supply a logical matrix of the

Hello list, I have 3 matrices with same dimension : > veca=matrix(1:25,5,5) > vecb=matrix(letters[1:25],5,5) > vecc=matrix(LETTERS[1:25],5,5) I would like to obtain a new matrix composed by alternating rows of these different matrices (row 1 of mat 1, row 1 of mat 2, row 1 of mat 3, row 2 of mat 1.....) I have found a solution to do it but it is not very pretty and I wonder if I