[Numpy-discussion] lstsq: masked arrays, weights, scaling, and covariance

josef.pktd@gmai... josef.pktd@gmai...
Sat Sep 17 14:40:13 CDT 2011


On Sat, Sep 17, 2011 at 2:52 PM, Charles R Harris
<charlesr.harris@gmail.com> wrote:
> Hi All,
>
> I'd like to start a discussion about modifications to lstsq to accommodate
> the new masked arrays and move weights, scaling, and covariance
> determination down to a lower common level. This is motivated by Travis'
> recent changes to polyfit as well as my own various polynomial fits that
> also allow weights. Also, once these features are pushed down to lstsq, it
> should be possible to push them down further into a c-wrapper for the LAPACK
> routines, which is where I really think they belong in the long run.
>
> Because missing values will effect the std/var/cov in the same way as
> weights of zero, I think support for missing values and weights go naturally
> together. Support for scaling and covariance are less closely tied, but they
> are both features I use all the time in practice and having them available
> will be useful.  It might also be nice to change the return signature,
> though this would require a new function. I rather like the idea of
> returning the coefficients and a dictionary, where everything not a
> coefficient gets stuffed into the dictionary. In this regard see also Denis
> Laxalde's proposal, something we might want to be consistent with.
>
> Thoughts?

What's the speed penalty if we just want to use numpy/scipy linalg as
a library and don't need any of the extra features?

As some of the discussions have shown it can be pretty expensive to
use linalg in loops.

Josef

>
> Chuck
>
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