similar to: symmetric matrix multiplication

Just to avoid possible confusion, let me correct a typo (at step [2] in the example below). Apologies! -----FW: <XFMail.111023084327.ted.harding at wlandres.net>----- Date: Sun, 23 Oct 2011 08:43:27 +0100 (BST) Sender: r-help-bounces at r-project.org From: (Ted Harding) <ted.harding at wlandres.net> To: r-help at r-project.org Subject: Re: [R] symmetric matrix multiplication On

Full_Name: cajo ter Braak Version: 2.1.1 OS: Windows Submission from: (NULL) (137.224.10.105) # I would like to attach the matrix C in the Rdata file; it is 50x50 and comes from a geostatistical problem (spherical covariogram) > rm(list=ls(all=TRUE)) > load(file= "test.eigen.Rdata") > ls() [1] "C" "eW" > > sym.check = max(abs(C - t(C))) # should

Is there any way to know how the "dmvt" function computes the hypergeometric function needed in the calculation for the density of multivariate t distribution? -- View this message in context: http://r.789695.n4.nabble.com/hypergeometric-function-in-mvtnorm-tp4483730p4483730.html Sent from the R help mailing list archive at Nabble.com.

I would presume this is another manifestation of what I reported (reproduced below) on 2003-12-01. cajo.terbraak at wur.nl wrote: >Full_Name: cajo ter Braak >Version: 2.1.1 >OS: Windows >Submission from: (NULL) (137.224.10.105) > > ># I would like to attach the matrix C in the Rdata file; it is 50x50 and comes >from a geostatistical problem (spherical covariogram) >

R-3.0.1 rev 62743, binary downloaded from CRAN just now; macosx 10.8.3 Hello, eigen(symmetric=TRUE) behaves strangely when given complex matrices. The following two lines define 'A', a 100x100 (real) symmetric matrix which theoretical considerations [Bochner's theorem] show to be positive definite: jj <- matrix(0,100,100) A <- exp(-0.1*(row(jj)-col(jj))^2) A's being

I am working with the pmt function in the {mnormt} package, and i am getting negative values returned. the following is an example of one of my outputs: pmt(x = c(3.024960, -1.010898), mean = c(21.18844, 21.18844), S = matrix(c(.319,.139,.139,0.319), 2, 2),df = 42) # -6.585641e-18 Any help on why i'm getting negative numbers would be very much appreciated. THanks! -- View this message in

from ?eigen symmetric: if 'TRUE', the matrix is assumed to be symmetric (or Hermitian if complex) and only its lower triangle is used. If 'symmetric' is not specified, the matrix is inspected for symmetry. I think that could mislead a naive reader as it suggests that, with symmetric=TRUE, the result of eigen() (vectors and values) depends only on

I am trying to use the dmt function in the package {mnormt}. Throughout my algorithm, the covariance matrix is sometime calculated to be singular. When attempting to calculate the dmt function with a covariance that is not positive definite, I would like it to return Inf or NaN instead of an error message. I have been using the try function, however it is not yeilding the desired result. (I did

While using the rmvnorm function, I get the error: Error in eigen(sigma, sym = TRUE) : error code 5 from Lapack routine 'dsyevr' The same thing happens when I try the eigen() function on my covariance matrix. The matrix is a symmetric 111x111 matrix. Well, it is almost symmetric; there are slight deviations from symmetry (the largest is 3e-18). I have this in an MCMC loop, and it

Hi, I have two products which are substitudes. I try to fix a system as below to mydata. Demand1 = A1 -B1*Price1 + C1*Price2 Demand2 = A2 +B2*Price1 - C2*Price2 I would expect C1 & B2 to be symmetric, If they are truly substitude. How can I enforce this symmetry when creating a system of equations via SystemFit ? -- View this message in context:

Dear R users, I am not good in R-language programming. So, i need your help. I want to convert my lower-triangle value of symmetry matrix into a vector with their row and column name. I found a function called "sm2vec" in "corpcor" package but it give only a vector of values but not row and column names. But i also want ROW and COLUMN name together with their corresponding

Hi all, Recently our statistics students noticed that their Gibbs samplers were crashing due to some NaNs in some parameters. The NaNs came from mvrnorm (Ripley & Venables' MASS package multivariate normal sampling function) and with some more investigation it turned out that they were generated by function eigen, the eigenvalue computing function. The problem did not seem to happen

Hello list, Sorry, these questions are not directly linked to R. If I consider an indefinte real matrix, I would like to know if the symmetry of the matrix is sufficient to say that their eigenvectors are real ? And what is the conditions to ensure that eigenvectors are real in the case of an asymmetric matrix (if some conditions exist)? Thanks in Advance, St?phane DRAY

Hi I need to use rep() to get a vector out, but I have spotted something very strange. See the reproducible example below. N <- 79 seg <- 5 segN <- N / seg # = 15.8 d1 <- seg - ( segN - floor(segN) ) * seg d1 # = 1 rep(2, d1) # = numeric(0), strange - why doesn't it print one "2"? rep(2, 1) # 2, ok rep(2, d1 / 1,1) # 2, this

Full_Name: Mike Danilov Version: 2.9.0 OS: Fedora Core 9 Submission from: (NULL) (142.103.121.198) When checking for the symmetry of a matrix, function isSymmetric.matrix() gets confused by the discrepancy of colnames/rownames if its argument. See the code snippet below. Perhaps it's a problem of the matrix product which copies colnames of the first argument but not the rownames of the

1. Martin Maechler's comments should be taken as replacements for anything I wrote where appropriate. Any apparent conflict is a result of his superior knowledge. 2. 'eigen' returns the eigenvalue decomposition assuming the matrix is symmetric, ignoring anything in m[upper.tri(m)]. 3. The basic idea behind both posdefify and nearPD is to compute the

Dear R users, even if this question is not related to an issue about R, probably some of you will be able to help me. I have a square matrix of dimension k by k with alpha on the diagonal and beta everywhee else. This symmetric matrix is called symmetric compound matrix and has the form a( I + cJ), where I is the k by k identity matrix J is the k by k matrix of all ones a = alpha - beta c =

Dear R experts, I really have difficulty when I try to deal with this question. suppose X is a square symmetric matrix. The exponent of X is defined by the matrix limit as following: exp(X) = lim (I + X/n)^n, note: the limit is from n to infinite. How can I write R function for the above? Thank you very much -- View this message in context:

Hello, How can I create a symmetric contingency table from two categorical vectors having different length of levels? For example one vector has 98 levels TotalData1$Taxa.1 [1] "Aconoidasida" "Actinobacteria (class)" "Actinopterygii" "Alphaproteobacteria" [5] "Amoebozoa"

Dear all r-users, I am getting a big problem with matrix multiplication suppose I have, > weight Weight 1 1067640 2 8871500 3 42948778 4 127583735 5 22000000 6 44000000 7 56850000 8 23805662 and, > s a b c d e f g h a 402493.18 -133931.62 461483.3 -94042.86 674493.8