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Using the Interpolate/Spline Functionality for regression splines

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  • Subject: [mg104387] Using the Interpolate/Spline Functionality for regression splines
  • From: "Blackwell, Keith" <Keith.Blackwell at rbccm.com>
  • Date: Fri, 30 Oct 2009 02:17:17 -0500 (EST)

Does anyone have any experience doing this?

I've been implementing regression splines on my own for a while and was
wondering if there was any way to speed things up / take advantage of
the functionality in mathematica to quickly switch constraints.

I thought of trying to embed interpolation or bspline into a findfit
function, but wasn't sure exactly how.


The basic problem is this.

I have an observed set of data OBS. I also know the entire set of yt and
ts

OBS[[t]] =  g[ f[ t ] , t , yt ] + random error


I want to use the interpolation/spline functionality to find the f[x]
that minimizes the squared prediction error.

Thanks in Advance,

Keith
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