Displaying 20 results from an estimated 10000 matches similar to: "solve vs. qr.solve"
2007 May 01
1
(PR#9623) qr.coef: permutes dimnames; inserts NA; promises
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
2019 Aug 13
0
behaviour and documentation of qr.solve
Greetings,
In my opinion the documentation or behaviour of qr.solve, qr.coef, qr.resid, and qr.fitted is not easily comprehensible and unfortunate.
We all know that a linear system Ax=b can have 0, one or infinitely many solutions. To treat all these cases uniformly we can rephrase the problem
as
x = argmin_u||Au-b||,
2007 May 15
3
qr.solve and lm
Dear R experts,
I have a Matlab code which I am translating to R in order to examine and
enhance it.
First of all, I need to reproduce in R the results which were already
obtained in Matlab (to make sure that everything is correct).
There are some matrix manipulations and '\' operation among them in the
code.
I have the following data frame
> ABS.df
Pro syn
2000 Apr 28
3
Matrix inverse
I haven't found a function that directly calculates the matrix inverse, does it exist? Otherwise what would be the fastest way to do it?
Patrik Waldmann
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2003 Oct 30
3
Change in 'solve' for r-patched
The solve function in r-patched has been changed so that it applies a
tolerance when using Lapack routines to calculate the inverse of a
matrix or to solve a system of linear equations. A tolerance has
always been used with the Linpack routines but not with the Lapack
routines in versions 1.7.x and 1.8.0. (You can use the optional
argument tol = 0 to override this check for computational
2007 May 15
2
QR Decompositon and qr.qty
Dear R people,
I do not have much knowledge about linear algebra but currently I need
to understand what the function qr.qty is actually doing. The
documentation states that it calculates t(Q) %*% y via a previously
performed QR matrix decomposition.
In order to do that, I tried following basic example:
m<-matrix(c(1,0,0,0,1,0,0,0,1,0,0,1),ncol=3) # 4x3 matrix
2012 Sep 07
1
Suggest adding a 'pivot' argument to qr.R
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:
2004 Jul 01
1
QR decomposition question
Hi all,
I wonder if this kind of questions are ok in this
list...
Quick question:
What does it mean than the rank of the QR
decomposition of a NxN matrix is N-1 ?
m: NxN matrix
qr(m)$rank equal to (N-1)
Long version:
I'm doing a manova on a matrix of 10 variables
and 16 observations.
> dim(tmp)
[1] 16 10
> fit <- manova( tmp ~ treatment*mouse )
>results <-
2003 Nov 12
2
bug in det using method="qr" (PR#1244) (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
2010 Feb 17
2
qr test?
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
2018 Jan 22
2
Inconsistent rank in qr()
Hi,
I have noticed different rank values calculated by qr() depending on
LAPACK parameter. When it is FALSE (default) a true rank is estimated and returned.
Unfortunately, when LAPACK is set to TRUE, the min(nrow(A), ncol(A)) is returned
which is only occasionally a true rank.
Would not it be more consistent to replace the rank in the latter case by something
based on the following pseudo code ?
2007 Apr 19
0
qr.coef: permutes dimnames; inserts NA; promises minimum-length (PR#9623)
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
2000 Mar 14
1
qr.solve (fwd)
Two friend reported me a problem, which I can't solve:
(I run R-1.0.0, Debian Linux)
They hava a function "corr.matrix" (see end of mail), and when they
create a 173x173 matrix with this function
V <- corr.matrix(0.3, n=173)
V1 <- qr.solve(V)
reports:
Error in qr(a, tol = tol) : NA/NaN/Inf in foreign function call (arg 1)
For n < 173, qr.solve returns the correct
1999 Jun 30
1
qr and Moore-Penrose
> Date: Wed, 30 Jun 1999 11:12:24 +0200 (MET DST)
> From: Torsten Hothorn <hothorn at amadeus.statistik.uni-dortmund.de>
>
> yesterday I had a little shock using qr (or lm). having a matrix
>
> X <- cbind(1,diag(3))
> y <- 1:3
>
> the qr.coef returns one NA (because X is singular). So I computed the
> Moore-Penrose inverse of X (just from the
2018 Jan 23
1
Inconsistent rank in qr()
Le 23/01/2018 ? 08:47, Martin Maechler a ?crit?:
>>>>>> 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
2018 Jan 22
3
Inconsistent rank in qr()
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 me a "full rank matrix" is a matrix the rank of which is indeed min(nrow(A), ncol(A))
but here the meaning of "always is full rank" is somewhat confusing. Does it
2004 Jul 01
1
QR decomposition and rank of a matrix
In summary.manova the qr decomposition of a NxN
matrix
is calculated and for some cases is giving me
a rank < N.
However, following suggestions of professor Ripley to
calculate the rank of a Matrix
On 7 Jun 2002, Brian Ripley wrote:
> For a more reliable answer, look at the SVD
> (function svd) and look at the
> singular values. For example (from lda.default)
X.s <-
2016 Oct 24
3
typo or stale info in qr man
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
```
2016 Apr 20
0
Solving sparse, singular systems of equations
This is kind of like asking for a solution to x+1=x+1. Go back to linear algebra and look up Singular Value Decomposition, and decide if you really want to proceed. See also ?svd and package irlba.
--
Sent from my phone. Please excuse my brevity.
On April 20, 2016 4:22:34 AM PDT, A A via R-help <r-help at r-project.org> wrote:
>
>
>
>I have a situation in R where I would like
2012 Dec 03
1
qr.qy and qr.qty give an error message when y is integer and LAPACK=TRUE
With this example
set.seed(123)
A <- matrix(runif(40), nrow = 8)
y <- 1:nrow(A)
A.laqr <- qr(A, LAPACK=TRUE)
both qr.qy(A.laqr,y) and qr.qty(A.laqr,y) give the respective error messages
Error in qr.qy(A.laqr, y) : 'b' must be a numeric matrix
Error in qr.qty(A.laqr, y) : 'b' must be a numeric matrix
However when Lapack is not used as in
A.liqr <- qr(A,