On Sat, Sep 17, 2011 at 1:40 PM, <josef.p...@gmail.com> wrote: > On Sat, Sep 17, 2011 at 2:52 PM, Charles R Harris > <charlesr.har...@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. > > I think the features should be optional and not the defaults, although masked arrays will always need some special treatment.
Chuck
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