similar to: Help : generating correlation matrix with a particular structure

************************************************************ Important: We would draw your attention to the notices at the bottom of this e-mail, particularly before opening and reviewing any file attachment(s). ************************************************************ Here is some code we have used. a<-array(c(1,.9,.7,.9,1,.3,.7,.3,1),dim=c(3,3)) a s<-eigen(a)$vectors

Hi all, I wonder if this kind of questions are ok in this list... Quick question: What does it mean than the rank of the QR decomposition of a NxN matrix is N-1 ? m: NxN matrix qr(m)$rank equal to (N-1) Long version: I'm doing a manova on a matrix of 10 variables and 16 observations. > dim(tmp) [1] 16 10 > fit <- manova( tmp ~ treatment*mouse ) >results <-

The code below create an nxn upper triangular matrix of one's. I'm stuck on finding a more efficient vectorized way - Thanks. --Dale n <- 9 data <- matrix(data=NA, nrow=n, ncol=n) data for (i in 1:n) { data[,i] <- c(rep(1,i), rep(0,n-i)) } data

Hi, I tried looking through google search on whether there's a way to computer the median for each row of a nxn matrix and return the medians for each row for further computation. And also if the number of columns in the matrix are even, how could I specify which median to use? Thank you very much! -- Edward Chen [[alternative HTML version deleted]]

Dear Rusers, Trying to reduce my for loops addiction, could somebody tell me if there are ways to simplify (and perhaps accelerate ?) the following line for (i in 1:N) for (j in 1:N) m[i,j] = b[i]-b[j]; (where m is a NxN matrix and b a vector of length N) Thanks for any hint.

Hello everyone I hope Im not bothering you all again. I have just begun to use R and so Im not yet familiarized with it.. I ve got an assignment which consists in calculating the area of a circle given a certain radius and center using the monte carlo method, which means that I have to plot a circle given its parameters. Limit the area inside it...with as many sample points as possible...and

Is there a function or an easier way to computer geometric means of each rows in a nxn matrix and spit out in an 1xn matrix ? -- Edward Chen [[alternative HTML version deleted]]

Hi all, Here is my problem: I have 3 matrices , A, B, C. Each is an nXn matrix. I need to create matrix D such that : D[i,j]= (A[i,j]+B[i,j]+C[i,j])/3. Being a newbie this is proving to be a challenge. Any ideas on how best to accomplish this? Thanks! Anjan -- ============================= anjan purkayastha, phd bioinformatics analyst whitehead institute for biomedical research nine cambridge

Hi Just a simple question really. I?ve got these large 2d matrices that I?d like to inspect, but not from start to finish. The head() command is convenient when columns are few. For large nxn matrices, however, head() and head.matrix() are still cumbersome. Is there a simple way of viewing both the columnwise and rowwise heads of a matrix? cheers, Bruce -- View this message in context:

Dear All, I am struggling with the following problem: I am given a NxN symmetric matrix P ( P[i,i]=0, i=1...N and P[i,j]>0 for i!=j) which stands for the relative distances of N points. I would like use it to get the coordinates of the N points in a 2D plane. Of course, the solution is not unique (given one solution, I can translate or rotate all the points by the same amount and generate

On 05.07.20 12:21, Roman Lebedev via llvm-dev wrote: > On Sun, Jul 5, 2020 at 12:18 PM Shawn Landden via llvm-dev > <llvm-dev at lists.llvm.org> wrote: >> >> >> >> Carry-less multiplication[1] instructions exist (at least optionally) on many architectures: armv8, RISC-V, x86_64, POWER, SPARC, C64x, and possibly more. >> >> This proposal is to add a

Dear all, I had to extracts/set elements from/in a matrix. Let say I have two vectors dim1 and dim2 of indices in the respective two dimensions of a matrix: I want to extract all the corresponding elements. I the case of a nxn matrix, dim1 <- 1:n and dim2 <- 1:n would extract the diagonal. I know one way would be to use the functions 'row' and 'col', but the matrixes I

Hi R-listers, I'm using R only for a few basic functions but am having difficulty doing something that *should* be simple. I have an nxn matrix, Q, where Q[i,j] is a directed value (in this case, oil exports from i to j). Note that Q[i,j]~=Q[j,i]. I imported column names along with the matrix then copied them to the rows using rownames(Q) <- colnames(Q). Simple so far. What I'd like

In summary.manova the qr decomposition of a NxN matrix is calculated and for some cases is giving me a rank < N. However, following suggestions of professor Ripley to calculate the rank of a Matrix On 7 Jun 2002, Brian Ripley wrote: > For a more reliable answer, look at the SVD > (function svd) and look at the > singular values. For example (from lda.default) X.s <-

Dear all, Is there a function in R that checks transitivity and acyclicity of a given nXn matrix with entries representing a decision-maker's comparisons of n objects? Like 0 1 0 1 1 1 0 0 0 1 0 0 1 0 0 0 1 1 0 0 1 0 0 0 0 1 0 1 0 1 0 1 0 1 0 0 1 represents xPy and 0 represents ~xPy. Is there a vectorized solution to this? n can be quite large. Thanks in advance, Alex

hi, i want to execute the following opimization problem: max r*w s.t.: w*z=1 # sum of w is 1 r, w are [nx1] vectors, z is a [nx1] vector consisting of 1 so far so good, works fine with lp the problem arises with the additional restriction w' * V * w where V is a [nxn] matrix how can i include this restriction since w arises twice? thanks, gg --

Hi, I got 1000 NxN matrices grouped in one array. I want one matrix in which p_ij is the average of all the 1000 matrices in the array. Here's what I'm trying to do: # P is the NxNx1000 array for(i in 1:N) for(j in 1:N) for(k in 1: 1000) mymat[ i, j ] <- mean( P [i , j , k ] ) Otherwise, I could have a NxNx1000 vector, and get the N^2 means of the 1+ (N^2)*(0: 999) elements. I

I wonder whether any of you know of an efficient way to calculate the approximate degrees of freedom of a gamm() fit. Calculating the smoother/projection matrix S: y -> \hat y and then its trace by sum(eigen(S))$values is what I've been doing so far- but I was hoping there might be a more efficient way than doing the spectral decomposition of an NxN-matrix. The degrees of freedom

I am using R for my bioinformatics research. I am dealing with a graph in which I need to find all possible path. I was looking for some package that solve my purpose but all in vain. There are available algorithms but most of them find shortest path that ignore other paths So I decided to write my own from scratch. I need to create a two dimensional matrix of size nXn. The element of each entry

Dear R-help list, Pls I have this problem. Suppose I have a matrix of size nxn say, generated as follows   z<-matrix(rnorm(n*n,0,1),nrow=n)   I want to write a function such that for i in 1:n, I will remove the rows and columns corresponding to i (so, will be left with n-1*n-1 submatrix in each cases). Now I need the sum of the determinant of each of this submatrices. As an example, if n=3, it