search for: detting

Hi R users, I am trying to use the optim function to maximize a likelihood funciton, and I got the following warning messages. Could anyone explain to me what messege 31 means exactly? Is it a cause for concern? Since the value of convergence turns out to be zero, it means that the converging is successful, right? So can I assume that the parameter estimates generated thereafter are reliable MLE

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, 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

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

I have been running into difficulties with dispatching on an S4 class defined in the SparseM package, when the method calls are inside a function passed as the f= argument to optimize() in functions in the spdep package. The S4 methods are typically defined as: setMethod("det","matrix.csr", function(x, ...) det(chol(x))^2) that is within setMethod() rather than by name before

Given the following data, I am plotting log.det ~ norm.beta, where the points depend on a parameter, lambda (but there is no functional form). I want to find the (x,y) positions along this curve corresponding to two special values of lambda lambda.HKB <- 0.004275357 lambda.LW <- 0.03229531 and draw reference lines at ~ -45 degrees (or normal to the curve) thru these points. How can I do

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

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

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,]

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

I have a function of two arguments, (m, n) that returns a list with the same structure as the function makefoo below. When m=1, it returns a list of vectors, each of length n. When m>1, it returns a list of square matrices, each of size m x m. makefoo <- function(m, n) { if (m==1) { A <- sample(1:100, n) B <- sample(1:100, n) C <- sample(1:100, n)

Hello, Is there a way to compare the relative relevance of fixed and random effects in mixed models? I have in mind measures of effect size in ANOVAs, and would like to obtain similar information with mixed models. Are there information criteria that allow to compare the relevance of each of the effects in a mixed model to the overall fit? Thank you, Bruno

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]]

We have a client machine (Windows 2000) that runs an application which spawns separate processes with each authenticate separately to the SAMBA server (3.0.13) When several of these processes run at the same time, SOME of the authentications fail with NT_STATUS_WRONG_PASSWORD written to the log.smbd file (error level 2)...I've attached a snippet of the log file to the end of this message All

Greetings; I've posted the following to R's bug tracking system (at https://bugs.r-project.org/bugzilla/show_bug.cgi?id=17210 ) and Martin Maechler requested that I post to this list as well. If I start R from the command line with --vanilla, then repeatedly execute the following line: det(matrix(nrow=10,ncol=10)) ... I eventually get a crash, with error: *** Error in

-----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

Hi, I have the following hypothetical optimization problem: -det(t(x-A%*%x1)%*%(x-A%*%x1)) where A,x,x1 are matrices. A coefficients and x and x1 are variable matrices or vectors. I tried to apply optim and nlm functions but I kept receive the following massage: Error in A%*%x1 : non-conformable arguments. The massage appears even the -det() can be calculated and the dimensions are checked. here

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

I'm confused by this: > identical(function() {}, function() {}) [1] FALSE Yet, after loading the Matrix package (which redefines det), the following is checked (in library.checkConflicts): > identical(get("det", baseenv()), get("det", asNamespace("Matrix")), ignore.environment=T) [1] TRUE I've looked at the code in identical.c and for closures it

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 =