[SciPy-Dev] Partial Least Squares Regression (PLSR) implementation

josef.pktd@gmai... josef.pktd@gmai...
Tue Oct 26 09:21:12 CDT 2010

On Tue, Oct 26, 2010 at 1:23 AM, Gael Varoquaux
<gael.varoquaux@normalesup.org> wrote:
> On Mon, Oct 25, 2010 at 10:24:48PM -0400, josef.pktd@gmail.com wrote:
>> Putting it in a public code repository for whatever is your favorite
>> version control system would be a good first step to share the code. A
>> pypi package or a scikits would be good depending on your plans for
>> it.
> It mights be good to have it in statsmodel, which is the reference scikit
> for statistical model :)

That was my first thought, and I would like to get this for statsmodels.
However, I'm not sure there is an easy way to integrate this right
now, and Skipper is busy with time series analysis and work, and I
have still a big backlog of things to get out of the sandbox.

It would be an extension, both to the support for control charts and
to regression with dimension reduction.
I looked a bit at the control chart literature when I was working on
structural break tests (e.g cusum test), and other stats packages have
support for this that we could or should also provide.
For regression with dimension reduction, we only have a principal
component regression example in the sandbox, but we haven't discussed
yet how it will fit in.

One option would be to add it to statsmodels.miscmodels which is for
models that look good (tested for standard usage cases), but don't
necessarily fit in yet with the rest.

If Aman sees a way to fit it into statsmodels, then I would be happy
to see something like this included, but otherwise I would prefer to
postpone this until we have cleaned up the current code sufficiently
for a new release.


> Gaël
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