similar to: using temporary arrays in R

useR's, I am writing a program in which the input can be multidimensional. As of now, to hold the input, I have created an n by m matrix where n is the number of observations and m is the number of variables. The data that I could potentially use can contain well over 20,000 observations. Can a simple matrix be used for this or would it be better and more efficient to create an external

I am moving this to r-devel. The problem and solution below posted on r-help could have been a bit slicker if %*% worked with multidimensional arrays multiplying them so that if the first arg is a multidimensional array it is mulitplied along the last dimension (and first dimension for the second arg). Then one could have written: Tbar <- tarray %*% t(wt) / rep(wti, each = 9) which is a bit

useR's I have a matrix from which I want to take multiple subsets from, according to a particular scheme I will now describe. The matrix below (mat) is 5x5, and I want to take 9 subsets of it, each of dimension 3x3. The best way to explain what the result should look like is with the following: > dat <- c(3,6,1,9,12,9,2,10,6,5,3,13,1,4,8,9,4,6,10,11,2,7,3,5,10) > miss <-

Hi, I recently encountered a problem with array subsetting and came up with a fix. Given an array of arbitrary dimensions, in which the number of dimensions is only known at runtime, I wanted to extract a subarray. The main issue with doing this is that in order to extract a subarray from an array of (say) 4 dimensions you usually specify something like this a.subarray <- a[,c(4,2),1:5,]

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, I am inquiring as to what are the best practices with respect to storing and manipulating ordered multi-dimensional arrays. For example, suppose I have a sequence of time-varying covariance matrices of asset returns. The data is ordered, but the ordering is not necessarily regular (e.g. daily data omitting weekends and holidays, etc.). The data array is say, N x N x T. For example, the

Consider the following data frame X <- data.frame(Titanic) Does anyone know of an easy way to convert X into a multidimensional array? Example that doesn't work X <- as.array(X, dim=c(4,2,2,2)) To do what I need, X needs to be converted into an array of dimensions c(4,2,2,2) in this case, not a table. Thanks in advance.

A student of mine wants to use R to do some nonmetric multidimensional scaling. According to the R FAQ, there's a package called pcurve that computes multidimensional scaling solutions, but I was not able to locate it the contrib page (I am a Windows user with R version 1.4.1). Can anyone tell me whether it is possible to do nonmetric multidimensional scaling with R, and if so, how? John

It's also very common in Fortran. -David Michael Ferguson via llvm-dev <llvm-dev at lists.llvm.org> writes: >> It seems that the main advantage of your proposal is that it would >> allow for non-constant strides (i.e. variable length arrays) in >> dimensions other than the first one. Do these appear frequently >> enough in the programs

Hi there I know, I'm sure you discussed this stuff 100 times, but I really have a basic understanding problem, if and how do I create a multidimensional array in R. I'm coming from MATLAB and there it's as easy as you ever could imagine. Ok, so, I want to have an array, where I can fill in data from a Excel spreadsheet. The array should be addressed like this:

Hello list. Another 'puzzle' for which I don't have a clean solution. Say I have a multidimensional object, e.g.: Mm<-matrix(1:6, nrow=2, dimnames=list(c("a","b"), c("g","h","i"))) And on the other hand I have a list Ind<-list("b","g") This holds, for each dimension, an indexer for that dimension. Now I would

> It seems that the main advantage of your proposal is that it would allow for non-constant strides (i.e. variable length arrays) in dimensions other than the first one. Do these appear frequently enough in the programs that you're interested in to be worth optimizing for? Yes - at least in Chapel (which is one of the motivating languages) these are very common. In other words, typical

On Aug 2, 2019, at 8:57 AM, Michael Kruse <llvmdev at meinersbur.de> wrote: >> This is why I ask whether its makes sense to add this to LLVM IR: If you want HPC style loop transformations, I don’t think that LLVM IR itself will ever be great, even with this. This might make some narrow set of cases slightly better, but this is far from a solution, and isn’t contiguous with getting to

We could also simply extend the existing inrange mechanism to non-constantexpr GEPs.  It would remove an inconsistency in the semantics, be relatively straight forward, and solve the motivating example. (I didn't read the proposal in full, so there may be other examples it doesn't solve.) Philip On 7/22/19 10:01 AM, Peter Collingbourne via llvm-dev wrote: > The restrictions of

Hi, anyone knows about any functions in R can get multidimensional integration not over a multidimensional rectangle (not adapt). For example, I tried the following function f(x,n)=x^n/n! phi.fun<-function(x,n) { if (n==1) { x }else{ integrate(phi.fun, lower=0, upper=x, n=n-1)$value } } I could get f(4,2)=4^2/2!=8, but failed in f(4,3)=4^3/3! Thanks Best, Lynette

On Wed, Sep 19, 2018 at 4:58 AM Venkataramanan Kumar < venkataramanan.kumar.llvm at gmail.com> wrote: > Hi, > > I tired to see when this behavior changed in LLVM. > It seems to start from. > --snip-- > commit 95e5d37d5868ebde2302bc302c1e0af407c5646d > Author: Sebastian Pop <sebpop at gmail.com> > Date: Tue Mar 6 21:55:59 2018 +0000 > > DA: remove

Dear list, I'm trying to add a new dim to a multidimensional array. My array looks like this a1 <- array(1:8, c(2, 2, 2)) dimnames(a1) <- list(A = c("A1", "A2"), B = c("B1", "B2"), D = c("D1", "D2")) I would like to add a new dim 'group' with the value "low".

Hello, May be somebody can help me... I am trying to find a solution of a convolution equation using fft (and unfortunately I do not have a good background for this). So I am just trying to figure out how it can be implemented in R. I have two multidimensional independent variables X and Z and I know their densities fx and fz, which are multidimensional arrays. So I have to find the density of

Hi, I am looking for some generalization of colSums and rowSums for general vector valued functions, and for arrays of more than 2 dimensions. So as a concrete example, suppose I have a 3 dimensional array, given by x = array(1:100,c(3,4,5)). and I want to sum the 3rd index of x to obain a 3 by 4 matrix. Using rowSums would return a vector of length 3 because it treats the last two indices as

I get some results back from running an iterative analysis in the form of a list of matrices. What I would like to do with this list is combine it such that all the similar components get combined into a multidimensional array. If possible I'd like to put results[[1]]$resultmean and results[[2]]$resultmean into a 3x3x2 array, and also put results[[1]]$resultsd and results[[2]]$resultsd in a