On Tue, 7 Jun 2022, Sven Schreiber wrote:
Am 06.06.2022 um 18:55 schrieb Cottrell, Allin:
Meanwhile (in git), you can now call QR with pivoting, the trigger
being a non-null third (matrix-pointer) argument.
For m < n (more rows) this seems to crash gretl. (I don't need it, but I
kind of
Am 06.06.2022 um 18:55 schrieb Cottrell, Allin:
Meanwhile (in git), you can now call QR with pivoting, the trigger
being a non-null third (matrix-pointer) argument.
For m < n (more rows) this seems to crash gretl. (I don't need it, but I
kind of thought it might cause trouble.)
cheers
sven
Am 06.06.2022 um 23:56 schrieb Cottrell, Allin:
On Mon, Jun 6, 2022 at 5:24 PM Sven Schreiber wrote:
OTOH, I ran some very crude and simple speed comparisons between
qrdecomp with and without pivoting (on Linux, current git), and
depending on the input the advantage could go either way it
On Mon, Jun 6, 2022 at 5:24 PM Sven Schreiber wrote:
>
> OTOH, I ran some very crude and simple speed comparisons between
> qrdecomp with and without pivoting (on Linux, current git), and
> depending on the input the advantage could go either way it seemed,
> which I found a little surprising.
On 06.06.22 22:33, Cottrell, Allin wrote:
Here's what I found: gretl's (SVD) rank() agrees with the numerical
rank values shown in the database. So do the results of counting
abs(R[i,i]) values from QR, provided the minimal value is in the range
1.0e-10 to 1.0e-8. Plain QR and QR with column
On Mon, Jun 6, 2022 at 12:13 PM Sven Schreiber wrote:
>
> What might be useful is to check out the database of singular matrices
> at San Jose State U. (It's astounding what things exist in science!)
Most of the matrices in that database are square. From the point of
view of libgretl I'm
On Mon, Jun 6, 2022 at 12:13 PM Sven Schreiber wrote:
>
> Am 06.06.2022 um 17:29 schrieb Cottrell, Allin:
>
> > Is there any general characterization of what it takes for plain QR
> > not to reveal rank?
> >
> > It would appear that the presence of all-zero rows and/or columns is
> > necessary
Am 06.06.2022 um 17:29 schrieb Cottrell, Allin:
Is there any general characterization of what it takes for plain QR
not to reveal rank?
It would appear that the presence of all-zero rows and/or columns is
necessary but not sufficient. With m > n you can construct mostly-zero
matrices where
On Mon, Jun 6, 2022 at 6:47 AM Sven Schreiber wrote:
>
> Am 06.06.2022 um 02:46 schrieb Cottrell, Allin:
> >
> > I tend to think these are different error conditions: (a) the input
> > contains exactly collinear data, and (b) one or more of the input
> > series/columns are all zero.
>
> But that
Am 06.06.2022 um 02:46 schrieb Cottrell, Allin:
On Sun, Jun 5, 2022 at 10:21 AM Riccardo (Jack) Lucchetti
wrote:
On Sun, 5 Jun 2022, Riccardo (Jack) Lucchetti wrote:
Very nice counterxample, Sven, kudos for that. Let me think about it.
Full disclosure: I didn't invent it myself, but found
On Sun, Jun 5, 2022 at 8:46 PM Cottrell, Allin wrote:
>
> I suppose dropcoll() could add a first check for any list element
> being all-zero. Though in most cases this would be a waste of time.
But also in most cases it won't cost much (since we should reject the
all-zeros condition quite
On Sun, Jun 5, 2022 at 10:21 AM Riccardo (Jack) Lucchetti
wrote:
>
> On Sun, 5 Jun 2022, Riccardo (Jack) Lucchetti wrote:
>
> > Very nice counterxample, Sven, kudos for that. Let me think about it.
>
> In fact this bug also affects the dropcoll() built-in function:
>
>
> nulldata 4
> series z =
On Sun, 5 Jun 2022, Riccardo (Jack) Lucchetti wrote:
Very nice counterxample, Sven, kudos for that. Let me think about it.
In fact this bug also affects the dropcoll() built-in function:
nulldata 4
series z = 0
series x = 1 | zeros($nobs - 1,1)
list X = z x
D = dropcoll(X)
list print D
So
On Sat, 4 Jun 2022, Sven Schreiber wrote:
Am 04.06.2022 um 15:51 schrieb Sven Schreiber:
Am 04.06.2022 um 13:11 schrieb Riccardo (Jack) Lucchetti:
On Fri, 3 Jun 2022, Cottrell, Allin wrote:
columns the execution time is not that different. Note: we currently
assess rank using regular QR,
Am 04.06.2022 um 15:51 schrieb Sven Schreiber:
Am 04.06.2022 um 13:11 schrieb Riccardo (Jack) Lucchetti:
On Fri, 3 Jun 2022, Cottrell, Allin wrote:
columns the execution time is not that different. Note: we currently
assess rank using regular QR, by counting the R elements greater than
some
Am 04.06.2022 um 13:11 schrieb Riccardo (Jack) Lucchetti:
On Fri, 3 Jun 2022, Cottrell, Allin wrote:
Maybe, though I gather that for a matrix with a lot more rows than
columns the execution time is not that different. Note: we currently
assess rank using regular QR, by counting the R
On Sat, 4 Jun 2022, Sven Schreiber wrote:
Am 03.06.2022 um 22:46 schrieb Cottrell, Allin:
Note: we currently assess rank using regular QR, by counting the
R elements greater than some specified "tiny" value.
Aha? The doc for "rank" says: "numerically computed via the singular
value
On Fri, 3 Jun 2022, Cottrell, Allin wrote:
On Fri, Jun 3, 2022 at 11:05 AM Sven Schreiber wrote:
I'm wondering whether it would be useful (or more precisely, whether the
cost-benefit calculation would be net positive...) to generalize the
qrdecomp() function to allow column pivoting. Here
Am 03.06.2022 um 22:46 schrieb Cottrell, Allin:
On Fri, Jun 3, 2022 at 11:05 AM Sven Schreiber wrote:
2) A QR decomposition with pivoting would provide a rank-revealing
operation. The natural workaround and alternative way to do this is SVD.
It is my understanding that SVD would be
On Fri, Jun 3, 2022 at 11:05 AM Sven Schreiber wrote:
>
> I'm wondering whether it would be useful (or more precisely, whether the
> cost-benefit calculation would be net positive...) to generalize the
> qrdecomp() function to allow column pivoting. Here are a couple of
> thoughts and remarks on
20 matches
Mail list logo
