[Numpy-discussion] introducing autoreg and autoregnn

Joseph Fox-Rabinovitz jfoxrabinovitz at gmail.com
Fri Jun 5 22:40:40 EDT 2020


Are you familiar with the lmfit project? I am not an expert, but it seems
like your algorithms may be useful there. I recommend checking with Matt
Newville via the mailing list.



On Fri, Jun 5, 2020, 17:00 Ralf Gommers <ralf.gommers at gmail.com> wrote:

> On Fri, Jun 5, 2020 at 9:48 PM rondall jones <rejones7 at msn.com> wrote:
>> Hello! I have supported constrained solvers for linear matrix problems
>> for about 10 years in C++, but have now switched to Python. I am going to
>> submit a couple of new routines for linalg called autoreg(A,b) and
>> autoregnn(A,b). They work just like lstsq(A,b) normally, but when they
>> detect that the problem is dominated by noise they revert to an automatic
>> regularization scheme that returns a better behaved result than one gets
>> from lstsq. In addition, autoregnn enforces a nonnegativity constraint on
>> the solution. I have put on my web site a slightly fuller featured version
>> of these same two algorithms, using a Class implementation to facilitate
>> retuning several diagnostic or other artifacts. The web site contains
>> tutorials on these methods and a number of examples of their use. See
>> http://www.rejones7.net/autorej/ . I hope this community can take a look
>> at these routines and see whether they are appropriate for linalg or should
>> be in another location.
> Hi Ron, thanks for proposing this. It seems out of scope for NumPy;
> scipy.linalg or scipy.optimize seem like the most obvious candidates.
> If you propose inclusion into SciPy, it would be good to discuss whether
> the algorithm is based on a publication showing usage via citation stats or
> some other way. There's more details at
> http://scipy.github.io/devdocs/dev/core-dev/index.html#deciding-on-new-features
> Cheers,
> Ralf
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