similar to: Help with R software

I have (below) an attempt at an R script to find the limit distribution of a continuous-time Markov process, using the formulae outlined at http://www.uwm.edu/~ziyu/ctc.pdf, page 5. First, is there a better exposition of a practical algorithm for doing this? I have not found an R package that does this specifically, nor anything on the web. Second, the script below will give the right

Hello,.. Apologies for the newbie question but... I have a matrix R, and I know that *B %*% t(b) = R* *I'm trying to solve for B *(aka. 'factoring the correlation matrix' I think) Please help! I've read that 'to solve for B we define the eigenvalues of R and then apply the techniques of Principal Component Analysis' This made me reach for princomp() but now I'm

Dear all, I encounter some covariance matrix with quite small eigenvalues (around 1e-18), which are smaller than the machine precision. The dimension of my matrix is 17. Here I just fake some small matrix for illustration. a<-diag(c(rep(3,4),1e-18)) # a matrix with small eigenvalues b<-matrix(1:25,ncol=5) # define b to get an orthogonal matrix b<-b+t(b) bb<-eigen(b,symmetric=T)

i am trying to use matinv from the Design package to compute the generalized inverse of the normal equations of a 3x3 design via the sweep operator. That is, for the linear model y = ? + x1 + x2 + x1*x2 where x1, x2 are 3-level factors and dummy coding is being used the matrix to be inverted is X'X = 9 3 3 3 3 3 3 1 1 1 1 1 1 1 1 1 3 3 0 0 1 1 1 1 0 0 1 0 0 1 0 0 3 0 3 0 1 1 1 0 1 0 0 1

Hi all, I have two matrices: G<-matrix(c(2.0, 0.5, 0.5, 0.5, 2.0, 0.5, 0.5, 0.5,2.0),3,3) P<-matrix(c(1.0, 0.5, 0.5, 0.5, 1.0, 0.5, 0.5, 0.5,1.0),3,3) and I want to run this equation to get a new matrix F: F = [P+2G]^-1/2 P [P+2G]^-1/2 Could someone please tell me how to code this in R? Many thanks in advance for your time. Best wishes, Matt [[alternative HTML version deleted]]

Hello List, i need help for eigen and svd functions. I have a non-symmetric square matrix. These matrix is not positive (some eigenvalues are negative). I want to diagonalise these matrix. So, I use svd and eigen and i compare the results. eigen give me the "good" eigenvalues (positive and negative). I compare with another software and the results are the same. BUT, when i use svd,

Hi, I need to raise a correlation matrix; R; to the negative one half power. i.e. I need to find R^(-1/2) eg: if R=[{1,.4},{.4,1}], then R^(-1/2)=[{1.0681,-.2229}, {-.2229,1.0681}]where matrix=[{row1},{row2}] And are there any built in functions to do this? mtx.exp doesn't work because it's not raised to a positive integer Thank you so much. -- View this message in context:

I have a simple system of linear equations to solve for X, aX=b: > a [,1] [,2] [,3] [,4] [1,] 1 2 1 1 [2,] 3 0 0 4 [3,] 1 -4 -2 -2 [4,] 0 0 0 0 > b [,1] [1,] 0 [2,] 2 [3,] 2 [4,] 0 (This is ex Ch1, 2.2 of Artin, Algebra). So, 3 eqs in 4 unknowns. One can easily use row-reductions to find a homogeneous solution(b=0) of: X_1

Dear Peter, thank you very much for your answer. My problem is that I need to calculate the following quantity: solve(chol(A)%*%Y) Y is a 3*3 diagonal matrix and A is a 3*3 matrix. Unfortunately one eigenvalue of A is negative. I can anyway take the square root of A but when I multiply it by Y, the imaginary part of the square root of A is dropped, and I do not get the right answer. I tried

List serv subscribers, I am wondering if there is an efficient means of doing recursive matrix multiplication in R. My data resides in a 4 X 2541 matrix from which I need to extract 2541 2X2 matrices based on each row. If I attempt something like this: function(AO) {A<-AO {for(t in 1:4)

Dear R Users, How can I prevent solve.Qp from printing the solution progress ? Thanks in advance, Tolga This email is confidential and subject to important disclaimers and conditions including on offers for the purchase or sale of securities, accuracy and completeness of information, viruses, confidentiality, legal privilege, and legal entity disclaimers, available at

General goal: Write R code to find the inverse matrix of an nxn positive definite symmetric matrix. Use solve() to verify your code works. Started with a 3x3 matrix example to build the code, but something dosen't seem to be working. I just don't know where I am going wrong. ##Example matrix I found online A<-c(4,1,-1,1,2,1,-1,1,2) m<-matrix(A,nrow=3,ncol=3) ##Caculate the eigen

Given a matrix B, where B=A'A, how can I find A? In other words, if I have a matrix B which I know is another matrix A times its transpose, can I find matrix A? Thanks, Mike

Is there any routine to obtain a g-inverse of a matrix in R or S-PLUS? Tapio Nummi University of Tampere Finland -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To:

I am trying to check the results from an Eigen decomposition and I need to force a scalar multiplication. The fundamental equation is: Ax = lx. Where 'l' is the eigen value and x is the eigen vector corresponding to the eigenvalue. 'R' returns the eigenvalues as a vector (e <- eigen(A); e$values). So in order to 'check' the result I would multiply the eigenvalues

Hi, I'm trying to use the solve() function in R to invert a matrix. I get the following error, "Lapack routine dgesv: system is exactly singular" However, My matrix doesn't appear to be singular. [,1] [,2] [,3] [,4] [1,] 0.99252358 0.93715047 0.7540535 0.4579895 [2,] 0.01607797 0.09616267 0.2452471 0.3088614 [3,] 0.09772828 0.58451468 1.4907090

Hi all, I'm looking for an analytic method to obtain the PDF & CDF of the sampling distribution of a given correlation (rho) at a given sample size (N). I've attached code describing a monte carlo method of achieving this, and while it is relatively fast, an analytic solution would obviously be optimal. get.cors <- function(i, x, y, N){ end=i*N

It works! But Once I have the square root of this matrix, how do I convert it to a real (not imaginary) matrix which has the same property? Is that possible? Best, Simon >----Messaggio originale---- >Da: p.dalgaard at biostat.ku.dk >Data: 21-nov-2009 18.56 >A: "Charles C. Berry"<cberry at tajo.ucsd.edu> >Cc: "simona.racioppi at

> Date: Sat, 8 Jun 2024 19:16:22 -0400 > From: Ben Bolker <bbolker at gmail.com> > > The ASAN errors occur *even if the zero-length object is not actually > accessed*/is used in a perfectly correct manner, i.e. it's perfectly > legal in base R to define `m <- numeric(0)` or `m <- matrix(nrow = 0, > ncol = 0)`, whereas doing the

I am trying to transpose a dataframe by its first column using the by statement using the t function. When I use the by function, I get a message, Error in FUN(X[[i]], ...) : could not find function "FUN" I don't think I have a syntax error in my by statement because the by statment works using the print function. Data and an executable example follows: phonydata2 <-