[SciPy-User] scipy.interpolate.rbf sensitive to input noise ?

[josef.pktd at gmail.com]

On Tue, Feb 23, 2010 at 12:46 PM, Robert Kern <robert.kern at gmail.com> wrote:
> On Tue, Feb 23, 2010 at 11:43, denis <denis-bz-gg at t-online.de> wrote:
>> Robert, Josef,
>>  thanks much for taking the time to look at RBF some more.
>> Summary, correct me:
>>    A - smooth*I in rbf.py is a sign error (ticket ?)
>
> Not necessarily. It seems to work well in at least some cases. Find a
> reference that says otherwise if you want it changed.

chapter 2 page 16, for gaussian process. As I said I don't know about
the other methods

http://docs.google.com/viewer?a=v&q=cache:qs8AaAxO6nkJ:www.gaussianprocess.org/gpml/chapters/RW2.pdf+gaussian+process+noise+Ridge&hl=en&gl=ca&pid=bl&srcid=ADGEESj4j8osT6cOIc65r3OaeAtQO_dzgZD4YxSAEkFTeRZajBcROJpJJ9zTlMSrD2OaK1iOJYgy8QqH_Nr0rNxf41faNihCdIzWyVOYxtCFIR7H8mdQZAKFoeaRkFamQlCKhp_s1FOI&sig=

www.gaussianprocess.org/gpml/chapters/RW2.pdf

Josef
>
>>    for gauss, start with A + 1e-6*I  to move eigenvalues away from 0
>>    others have pos/neg eigenvalues, don't need smooth.
>
> No. If you need a smoothed approximation to noisy data rather than
> exact interpolation than you use the smooth keyword. Otherwise, you
> don't.
>
> --
> Robert Kern
>
> "I have come to believe that the whole world is an enigma, a harmless
> enigma that is made terrible by our own mad attempt to interpret it as
> though it had an underlying truth."
>  -- Umberto Eco
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