similar to: (PR#4450)

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

On Mon, Dec 11, 2017 at 3:37 PM, Mikhail Zolotukhin via cfe-dev < cfe-dev at lists.llvm.org> wrote: > Hi Kim, > > On Dec 10, 2017, at 7:39 AM, Kim Gräsman <kim.grasman at gmail.com> wrote: > > Hi Michael, > > On Thu, Dec 7, 2017 at 3:16 AM, Michael Zolotukhin > <mzolotukhin at apple.com> wrote: > > > Nice to IWYU developers here:) I wonder how

That's excellent! I think the check-sanitizer target should cover it. Thanks, Hans On Fri, Feb 22, 2019 at 1:34 PM Kim Gräsman <kim.grasman at gmail.com> wrote: > > Hi Hans, > > I have a freebsd machine and some time to spare this weekend. > > Could you offer the minimal git bisect command to repro? I'm hoping not to have to run the full check-clang test suite if

Hi Michael, On Thu, Dec 7, 2017 at 3:16 AM, Michael Zolotukhin <mzolotukhin at apple.com> wrote: > > Nice to IWYU developers here:) I wonder how hard it would be to run IWYU on > LLVM/Clang (or, if it’s supposed to work, I wonder what I did wrong). There are known problems with running IWYU over LLVM/Clang -- Zachary Turner made an attempt a while back to get it up and running.

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

Hello, Currently, determinant(A) calculates the determinant of 'A' by factorizing A=LU and computing prod(diag(U)) [or the logarithm of the absolute value]. The factorization is done by LAPACK routine DGETRF, which gives a status code INFO, documented [1] as follows: *> INFO is INTEGER *> = 0: successful exit *> < 0: if INFO = -i, the i-th

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;

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]]

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

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 =

I'm a little late to the party, but one observation that I haven't seen mentioned is that simply removing #includes and testing that the program compiles is not guaranteed to be a correct transformation. Imagine, for example, that a header file provides an overload of a function that is a better match than one found elsewhere. It will compile either way, but without the #include, you

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 --

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

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<-

[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

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

-----Original Message----- From: R-SIG-Debian [mailto:r-sig-debian-bounces at r-project.org] On Behalf Of Rolf Turner Sent: Thursday, 19 January 2017 10:11 AM To: Ian Erickson Cc: r-sig-debian at r-project.org Subject: Re: [R-sig-Debian] [FORGED] Taking determinant of a matrix of NAs results in intermittent memory corruption >On 19/01/17 11:54, Ian Erickson wrote: >> Greetings; I've

On Tue, 14 Aug 2018 at 11:56, Kim Gräsman <kim.grasman at gmail.com> wrote: > > On Tue, Aug 14, 2018 at 11:51 AM Andrew Haley <aph at redhat.com> wrote: > > > > On 08/12/2018 02:19 PM, Kim Gräsman wrote: > > > I still feel a little uncomfortable, because I think Jonathan makes an > > > excellent point -- if GCC thinks there's a strict-aliasing

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

Many thanks for digging into this, and sorry for my slow reply. Kamil: it sounds like your commit is involved here. Any idea what's happening? Dimitry: If we don't find anyone to debug and fix this before the release, how bad is it for FreeBSD? Can it be worked around downstream if 8.0.0 ships without a fix? Since I'm not entirely sure how supported this functionality is on FreeBSD,