similar to: row-echelon form (was no subject)

Hi everyone, I am looking to use R as a MATLAB replacement for linear algebra. I've done a fairly good job for finding replacements for most of the functions I'm interested in, I John Fox wrote a program for implementing the reduced row echelon form of a matrix (by doing the Gauss-Jordan elimination). I modified it a bit: rref <- function(A,

how to produce a Row Reduced Echelon Form for a matrix in R? Aimin Yan

I am testing 'qr' with an admittedly contrived matrix and I am getting different results than I am from another package. The matrix that I am using is: x <- matrix(seq(.1, by=.1, length.out=12), 4) So the whole test is: x <- matrix(seq(.1, by=.1, length.out=12), 4) qr(x) And the output from 'R' is: $qr [,1] [,2] [,3] [1,] -0.5477226 -1.2780193

I suggest adding a 'pivot' argument to qr.R, to obtain columns in the same order as the original x, so that a <- qr(x) qr.Q(a) %*% qr.R(a, pivot=TRUE) returns x. -------------------------------------------------- # File src/library/base/R/qr.R qr.R <- function(qr, complete = FALSE, pivot = FALSE) { # Args: # qr: a QR decomposition, produced by qr() # complete:

Here is a modified version of qraux.Rd, an edited version of R-2.14.0/src/library/base/man/qraux.Rd This gives some details and an example for the case of pivoting. In this case, it is not true that X = QR; rather X[, pivot] = QR. It may save some other people bugs and time to have this information. Tim Hesterberg -------------------------------------------------- % File

Full_Name: Christian Brechbuehler Version: 2.4.1 Patched (2007-03-25 r40917) OS: Linux 2.6.15-27-adm64-xeon; Ubuntu 6.06.1 LTS Submission from: (NULL) (24.61.47.236) Splus and R have different ideas about what qr.coef(qr()) should return, which is fine... but I believe that R has a bug in that it is not internally consistent, and another separate bug in the documentation. In particular, on

On Thu, 19 Apr 2007, brech at delphioutpost.com wrote: > Full_Name: Christian Brechbuehler > Version: 2.4.1 Patched (2007-03-25 r40917) > OS: Linux 2.6.15-27-adm64-xeon; Ubuntu 6.06.1 LTS > Submission from: (NULL) (24.61.47.236) > > > Splus and R have different ideas about what qr.coef(qr()) should return, > which is fine... but I believe that R has a bug in that it is not

I am using 2.2.0 If the QR decomposition of an N*M matrix is such that the pivoting order is not 1:M, Q%*%R does not result in the original matrix but in a matrix with the columns permuted. This is clearly intentional, and probably to be expected if pivoting is used --- chol() behaves in the same manner (it would perhaps be nice if the qr help page made that clear in the same way that the chol()

Dear list, Can anyone tell me how to obtain the rank of a sparse Matrix, for example from package Matrix (class dgCMatrix)? Here is an example of QR decomposition of a sparse matrix (from the sparseQR class help). library(Matrix) data(KNex) mm <- KNex$mm str(mmQR <- qr(mm)) Similarly, using the functions/classes from the relatively new MatrixModels package: library(MatrixModels)

I was looking for an R-package that would reduce matrices to row-echelon form, but Google was not my friend; any leads? If not, I wonder if the problem could be expressed in terms of constraint satisfaction...

R-users E-mail: r-help@r-project.org I have a quenstion on "gam()" in "gam" package. The help of gam() says: 'gam' uses the _backfitting algorithm_ to combine different smoothing or fitting methods. On the other hand, lm.wfit(), which is a routine of gam.fit() contains: z <- .Fortran("dqrls", qr = x * wts, n = n, p = p, y = y *

R-users E-mail: r-help@r-project.org I have a quenstion on "gam()" in "gam" package. The help of gam() says: 'gam' uses the _backfitting algorithm_ to combine different smoothing or fitting methods. On the other hand, lm.wfit(), which is a routine of gam.fit() contains: z <- .Fortran("dqrls", qr = x * wts, n = n, p = p, y = y *

Hello. I am trying to invert a matrix, and I am finding that I can get different answers depending on whether I set LAPACK true or false using "qr". I had understood that LAPACK is, in general more robust and faster than LINPACK, so I am confused as to why I am getting what seems to be invalid answers. The matrix is ostensibly the Hessian for a function I am optimizing. I want to get

The bug I submitted yesterday (It's not entered in the bug data base, so I have no ID for it) included a suggested fix that is not correct. It worked for the examples I gave because there was no pivoting in fact, or only pivot permutations that were idempotent. A correction that works in general on the examples I gave makes these two changes in qr.coef(): ## coef[qr$pivot, ]

Hello I have a 3x3 matrix (A), which I would have to reduce to Reduced Row echelon form.  Besides, at every iteration k, the elementary row matrix Ek has to be printed and also print the product of sum Ei (i=1 to k) and A. Any ideas how to go about doing this. KS. [[alternative HTML version deleted]]

man for `qr` says that the function uses LINPACK's DQRDC, while it in fact uses DQRDC2. ``` The QR decomposition of the matrix as computed by LINPACK or LAPACK. The components in the returned value correspond directly to the values returned by DQRDC/DGEQP3/ZGEQP3 ```

Let's assume that the columns of the model matrix, apart perhaps from an initial column that corresponds to the overall mean, have been centred. Then: 1) Normal equation methods give an accurate fit to the matrix of centred sums of squares and products. 2) QR methods give an accurate fit to the predicted values. QR will give better precision than normal equation methods (e.g., Cholesky) if

Full_Name: Rick Sayre Version: 2.8.0 OS: windows, linux, os x Submission from: (NULL) (138.72.153.166) PR#8476 and PR#8478 http://bugs.r-project.org/cgi-bin/R/Models-fixed?id=8478 http://bugs.r-project.org/cgi-bin/R/Models-fixed?id=8476 discuss fixing qr.coef to handle complex matrices correctly But it appears the solution now "shipping" only handles square matrices. In 2.8.0 [linux,

>>>>> Serguei Sokol <sokol at insa-toulouse.fr> >>>>> on Mon, 22 Jan 2018 17:57:47 +0100 writes: > Le 22/01/2018 ? 17:40, Keith O'Hara a ?crit?: >> This behavior is noted in the qr documentation, no? >> >> rank - the rank of x as computed by the decomposition(*): always full rank in the LAPACK case. > For a

This behavior is noted in the qr documentation, no? rank - the rank of x as computed by the decomposition(*): always full rank in the LAPACK case. > On Jan 22, 2018, at 11:21 AM, Serguei Sokol <sokol at insa-toulouse.fr> wrote: > > Hi, > > I have noticed different rank values calculated by qr() depending on > LAPACK parameter. When it is FALSE (default) a true rank is