search for: nxm

Hello, I am trying to find a permutation test that works on a general nxm table. The data set is small enough to have cells with too small counts to make chi2-approximation invalid. If the table was a 2x2 contingency table I would like to use a Fsher exact test (fisher.test) but that wont work in this general table. Does there exist a general function for this test. Be...

...riate observation, so each bootstrap sample would be an n x m matrix, and on each sample I want to calculate the n x n matrix. This task can be done with the sample function, but I would like to use the boot() function. I hope that it is going to be faster. Something like this: f1 <- function(nxm.matrix){...; return(nxn.matrix)} f2 <- function(nxm.matrix, i) f1(nxm.matrix[i,]) boot.out <- boot(nxm.matrix, R, f2) Error: incorrect number of subscripts on matrix Since the final goal would be to put a confidence interval on the statistics in each cell of the matrix I would like to use th...

Given an nxm matrix A I want to compute the nxm matrix B whose ij-th element is the sum of the elements of A lying on the diagonal that ends with element ij, i.e., b_ij = a_ij + a_(i-1)(j-1) + a_(i-2)(j-2) + ... In APL (which I no longer use), I would use the 'rotate' operator to derive an arr...

...mization. I would like to ask if there is R-function/package for solving the problem below: Minimize sum(abs(exp^(Ai1 x1 + Ai2 x2 + ... + Aim xm - bi) - 1)), for each i = 1, ..., n. subject to Ai1 x1 + Ai2 x2 + ... + Ajm xm - bi <= c, where c is a scalar. (x is a vector of variables, A is nxm matrix, b is a vector) [[alternative HTML version deleted]]

I am trying to write an efficient function that will do the following: Given an nxm matrix, 10 rows (observations) by 10 columns (samples) for each row, test of all values in the row are greater than a value k If all values are greater than k, then set all values to NA (or something), Return an nxm matrix with the modified rows. If I do this with a matrix of 20,000 rows, I will...

Dear R listers, Just a simple question. If we say an nxm matrix (n>m) is full rank of m, does this mean that this matrix has linearly independent columns? They are the same definition or needs some proof? Thanks for your answer. Fred [[alternative HTML version deleted]]

...ifferentiate instance types? From your code, it looks as if you’re implementing an inverted vtable structure, where there is a per-method vtable with per-subclass entries, rather than a traditional vtable where you have one per class and per-method entries. Your total vtable space goes from being NxM to being MxN, which doesn’t sound like an improvement. This kind of approach is generally popular in late-bound dynamic languages with duck typing where you have a lot of methods with few overrides and it’s worth having a slightly more expensive lookup to have a sparser structure than the full NxM...

Hi. I am aware of three different R packages for linear programming: glpk, linprog, lpSolve. From what I can tell, if there are N variables and M constraints, all these solvers require the full NxM constraint matrix. Some linear solvers I know of (not in R) have a sparse matrix input format. Are there any linear solvers in R that have a sparse matrix input format? (including the possibility of glpk, linprog, and lpSolve, in case I might have missed something in the documentation). Tha...

...mean etc) to get some analysis? I'd be very thankfull for some of your thoughts about "approaches". Now the question: I'm trying to build a vector with n entries, each consisting of the mean of m random numbers (exponential distributed for example). My approach was to construct a nxm random matrix and then to somehow take the mean of each row. But in the mean function there is no parameter to do this, so the intended approach of R is probably different.. any ideas? =) Richard -- View this message in context: http://r.789695.n4.nabble.com/calculating-the-mean-of-a-random-matri...

Hello, In an effort to help LLVM-style projects save memory, I’ve been toying with some macros that provide an alternative to C++ vtables that use LLVM-style RTTI design patterns instead. Is this something that LLVM or sub-projects think is worth pursuing? Or are the macros below too ugly/problematic? Feedback would be appreciated. Thanks, Dave //===- llvm/Support/VTable.h - LLVM-style

Hi, I am trying to creat a matrix with diagnal blocks, say, I have a matrix X of any dimension (nxm) ,and would like to have: X X X...

Hi all, Imagine I have a matrix G with N rows and M columns So L=NxM is the number of different cells in my matrix. I want to create a column vector F whose size will be F(L,1) So the fisrt row in F is G(1,1) Second row in F is G(1,2) When we arrive to a point M the element M+1 will be G(2, 1) Element M+2 will be G(2,2) and so on. I´m trying but allways error......

Dear All, I need to write 'n' functions on 'm' variables. The functions should be constructed according to the values of an (nxm) matrix of '1/0' values as follows. For example, if row1 is equal to ,say [1 0 .......0 0] then f1 <- (1+x1) if row 2 is equal to, say [1 1 1 0...0 1] then f2 <-(1+x1)*(1+x2)*(1+x3)*(1+xm) if row n is equal to [0 1 0 1 1 0 ..... 0] then fn <-(1+x2)*(1+x4)*(1+x5) Is there an effi...

Dear All, I have come upon an R-mode PCA protocol that uses the following arguments, where "mydata.txt" is an nxm matrix of n objects and m variables: > a <- read.table("mydata.txt") > b <- t(a) > c <- prcomp(b) > c$rotation The user then plots the coordinates given by c$rotation (PC1 and PC2) as the "scores" of their PCA plot. This doesn't make sense to me as th...

I need to multiply to very large, nonsparse matrices, and so get the error "allocMatrix: too many elements specified". Is there a way to set the limit for allocMatrix? In my case, the two matrices, A and B, are nxm and mxp where m is small, so I could subdivide each into blocks of submatrices A=rbind(A1,A2,...) and B=cbind(B1,B2,...) then multiply each pair of submatrices, but I was thinking there must be a better way to get around the allocMatrix limit. I'd be grateful for any suggestions! Thanks, Dav...

...e name: ### filename.arbre ### source("cophmatrix.r") ### cophmatrix <- function(){ library(mva) library(sm) nom <- ask(message="Name of the file") nbre <- ask(message="Number of sounds") quest <- ask(message="Matrix of dissimilarity (1) or nxm matrix (2)") fichier <- read.table(nom) ## matrix nxn ou nxm ## proximity between objects: nxn or description of n objects with m attributes if(quest == 1){ dis1 <- as.dist(fichier) } else{ methode <- ask(message="The distance measure to be used = euclidean:1...

Hi, I was trying to evaluate the pearson correlation and the p-values for an nxm matrix, where each row represents a vector. One way to do it would be to iterate through each row, and find its correlation value( and the p-value) with respect to the other rows. Is there some function by which I can use the matrix as input? Ideally, the output would be an nxn matrix, containing t...

I am using read.table to import a text file within R.   There are several "errors" in my text file.  An "extra" quotation mark has inadvertently been included within a few text fields.   e.g. for a pipe (|) delimited text file, I have something similar to this:   1|7|30| "dog" 2|6|25| ""cat" 3|4|20|"" 4|5| 56| "mouse" 5|3|56|

...adigms. There is interest in supporting OpenACC, for example, which > will require data copying clauses, and it would make sense to share > as much of the infrastructure as possible with OpenMP. Are you > interested in providing Cilk support as well? We probably don't want to > have NxM slightly-different ways of expressing 'this is a parallel > region'. There are obviously cases in which things need to be specific > to the interface (like runtime loop scheduling in OpenMP which implies > a specific interaction with the runtime library), but such cases may be >...

Hi based on some code from Thomas Petzoldt, I have a question: --- opar <- par(mfrow = c(2,4)) slices <- 8 m <- matrix(runif(100),10,10) my.list <- list() for (slice in 1:slices) { my.list[[slice]] <- m } for (slice in 1:slices) { x <- 1*(1:25) y <- 1*(1:25) z <- my.list[[slice]] image(list(x = 0:9, y = 0:9, z = z)) } par(opar) #restore device