similar to: det(diag(c(NaN, 1))) should be NaN, not 0

Hi, Which R function I should use to obtain determinant of a matrix with real(and complex) numbers? Kalin --------------------------------- Never miss a thing. Make Yahoo your homepage. [[alternative HTML version deleted]]

I just detected, that det() is not working on complex matrices any more, due to the fix to the bug reports noted above. I am not happy with this, as determinants are perfectly usable on complex matrices. AFAIUI the bugs resulted from less than optimal behaviour of qr() in certain cases. IMHO this is due to the unhappy decision to use a default for parameter tol to decide whether the the

r-devel list, I have recently written an R package that solves a linear least squares problem, and computes the multivariate normal density function. The bulk of the code is written in C, with interfacing code to the BLAS and Lapack libraries. The motivation here is speed. I ran into a problem computing the determinant of a symmetric matrix in packed storage. Apparently, there are no explicit

On 21/03/2005, at 10:09 PM, David Firth wrote: > I am sorry that I wasn't clear. All that I meant was that *this* > problem can result in different behaviour in "ordinary" statistical > applications. For example, if the objective function in a call to > optim() involves calling one of these linear algebra routines, the > result may be NaN (on systems other than Mac

Hello, I am trying to write an R package for doing analysis of speaker recognition systems. The big thing in this line of research is a DET-plot (detection Error Trade-off, a ROC plot with qnorm() warped axes). My approach has been to make a class "det" and also a function "det()" that will prepare the data into the right class. Now loading the library doesn't like me

Hello, When I use det() and qr() on complex matrices the result is in some cases indeterministic. The documentation speaks of numeric matrices (and not of complex matrices) but det() uses qr() which should handle complex matrices correctly. I've also tried using only qr() with similar results. det() returns a value that is not the determinant of the complex matrix (in accordance with

Hi uRsers, when inverting a 2 by 2 matrix using solve, I encountered a error message: solve.default(sigma, tol = 1e-07) : system is computationally singular: reciprocal condition number = 1.7671e-017 and then I test the determinant of this matrix: 6.341393e-06. In my program, I have a condition block that whether a matrix is invertible like this: if(det(sigma)<1e-7) return NULL;

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 =

Full_Name: Armin Roehrl Version: 1.4.0(2001-12-19) OS: Linux; Suse 7.3 Submission from: (NULL) (217.84.18.204) Hello, On a given matrix det returns different results whether I use the method "qr" or "eivenvalues". The matrix: > m2 [,1] [,2] [,3] [1,] 9.822616e+09 3.841723e+09 79790.09 [2,] 3.841723e+09 1.502536e+09 31251.82 [3,]

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

No, blas/veclib is tested, so aprt this extreme case you should report some other more commonly used cases in which something fails on OS X. This will help us to work it out. As said, I'll try some tests without using veclib and let you know. I've fowarded this mail to r-devel, which seems to be the right place, so for future msg on the subject please use r-devel. stefano On

Dear R, If I have remembered correctly, a square matrix is singular if and only if its determinant is zero. I am a bit confused by the following code error. Can someone give me a hint? > a <- matrix(c(1e20,1e2,1e3,1e3),2) > det(a) [1] 1e+23 > solve(a) Error in solve.default(a) : system is computationally singular: reciprocal condition number = 1e-17 Thanks in advance! Feng --

[Hope this is the right list where to send...] An attempt to update package 'mnormt' involves the addition of a small new function called 'pd.solve'. When I come to the package checking stage, an error occurs in parsing pd.solve.Rd. The full transcript of the outcome is copied below (it includes details on my installation) but the critical point is where the \examples{} section

Dear R-users, a question concerning sparse matrices in package "spam" (spam_0.29-2). On one hand I have a spam object (n X n) from which I cannot compute the inverse. On the other hand, if I convert this object in a plain matrix, I can find the inverse without any problem. Specifically I get the following error message: Error in chol.spam(a, ...) : Singularity problem when

On April 15th, Elizabeth wrote: <snip> > In execises 39-42, determine if the columns of the matrix span > R4: <snip> >(or x <- matrix(data=c(7, -5, 6, -7, 2, -3, 10, 9, -5, > 4, -2, 2, 8, -9, 7, 15), nrow=4, ncol=4) > >That is the whole of the question <snip> Have you tried det(x) and/or eigen(x) ? A zero determinant (within

Hi there, Could anyone please help me to understand what should be done in order not to get this error message: Error: evaluation nested too deeply: infinite recursion / options(expressions=)? Here is my code: determinant<- function(x){det(matrix(c(1.0,0.2,0.5,0.8,0.2,1.0,0.5,0.6,0.5,0.5,0.5,1.0,x,0.8,0.6,x,1.0),ncol=4,byrow=T))} matrix<-

I discovered recently that the phrase "Oja median" produces no hits in Jonathan Baron's very valuable R search engine. I found this surprising since I've long regarded this idea as one of the more interesting notions in the multivariate robustness literature. To begin to remedy this oversight I wrote a bivariate version and then decided that writing a general p-variate version

Full_Name: Krzysztof Podgorski Version: R version 2.4.1 (2006-12-18) OS: Windows XP Submission from: (NULL) (130.235.3.79) The function ''det'' works improperly for a singular matrix and returns a non-zero value even if ''solve'' reports singularity. The matrix is very simple as shown below. A <- diag(rep(c(64,8), c(8,8))) A[9:16,1] <- 8 A[1,9:16] <- 8

I am using C code to create an S4 object based on Douglas Bates's example in his lecture notes on <http://www.ci.tuwien.ac.at/Conferences/DSC-2003/Tutorials/RExtensions/slide s.pdf> http://www.ci.tuwien.ac.at/Conferences/DSC-2003/Tutorials/RExtensions/slides .pdf e.g. SEXP La_DGE_dc(SEXP A) { SEXP aa = PROTECT(duplicate(A)); SEXP adims, pivot, val; int

Dear R-devel, I am trying to use Fortran DGESV subroutine into C. Here it is the relevant part of the C file I am currently writing #include<stdio.h> #include<R.h> #include<Rmath.h> #include<math.h> void F77_NAME(DGESV)( int*, int*, double*, int*, int*, double*, int*, int*); void solve( int *p, double *A, double *Ainv) { ... F77_CALL(DGESV)(p, p, Ain, p, ipiv,