Mauro Talevi wrote:
Phil,
Phil Steitz wrote:
I think R uses QR as described above. Comments or suggestions for
other default implementations are most welcome. We should aim to
provide a default implementation that is reasonably fast and provides
good numerics across a broad range of design
Phil Steitz wrote:
Perhaps it would help if we had overloaded newData methods that accept
different input strategies, but ultimately they will produce a n x m
double array. That way we can provide users with choice.
I was thinking the same thing. The bit that is troubling me is the
omega matr
Phil,
Phil Steitz wrote:
I think R uses QR as described above. Comments or suggestions for other
default implementations are most welcome. We should aim to provide a
default implementation that is reasonably fast and provides good
numerics across a broad range of design matrices.
Got aroun
Phil Steitz wrote:
No, just X. see the references here:
http://apache.markmail.org/message/3aybm5emimg5da42
I think R uses QR as described above. Comments or suggestions for other
default implementations are most welcome. We should aim to provide a
default implementation that is reasonably
Mauro Talevi wrote:
Phil Steitz wrote:
Yes, and I would distinguish performance optimization from numerical
accuracy. From my perspective, we can release a ".0" with room for
performance improvement, but at least decent numerics are required.
I agree that decent numerics are required. I'm
Phil Steitz wrote:
Yes, and I would distinguish performance optimization from numerical
accuracy. From my perspective, we can release a ".0" with room for
performance improvement, but at least decent numerics are required.
I agree that decent numerics are required. I'm still rather surpris
Mauro Talevi wrote:
Hi Phil,
thanks for reviewing the multiple linear regression implementations
and setting up the R/NIST data tests. I finally got around to
installing R and can now run them too.
Phil Steitz wrote:
While clear and elegant from a matrix algebra standpoint, the
"nailve" i
Hi Phil,
thanks for reviewing the multiple linear regression implementations and
setting up the R/NIST data tests. I finally got around to installing R
and can now run them too.
Phil Steitz wrote:
While clear and elegant from a matrix algebra standpoint, the "nailve"
implementation in OLSM
While clear and elegant from a matrix algebra standpoint, the "nailve"
implementation in OLSMultipleLinearRegression has bad numerical
qualities. It is well known that solving the normal equations directly
does not give good numerics. I just added some tests to actually verify
parameter value
