[SciPy-User] weighted griddata

Christopher Barker Chris.Barker@noaa....
Fri Sep 17 14:00:35 CDT 2010


Adam Ryan wrote:
> For clarification, all the points of a line have the same t value, but
> each point has a weight of 0 to 1.


does that mean the ones with weight 0 you want to ignore, and ones with 
weight 1 you want to fit exactly? i.e. you know which ones are more 
robust/accurate?

If so then it doesn't sound to me like any of the smoothing routines 
being talked about are going to do the right thing, at least not out of 
the box -- I think they all assume that all points are equally valid, 
and weight according to how far away points are, or, more generally, how 
well they fit a smooth function.

Of the top of me head, I imagine you may be able to do some sort of 
least squares type fit to a known function (maybe a polynomial or 
piecewise-polynomial), but with the error term weighted according to to 
your known weights. That could look a lot like a spline fit, but you'd 
have to insert your weighting in there somehow.

-Chris






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Christopher Barker, Ph.D.
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