[SciPy-User] weighted griddata
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
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.
Christopher Barker, Ph.D.
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