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
