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Re: st: Regression analysis with a minimum function on the RHS


From   Austin Nichols <austinnichols@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Regression analysis with a minimum function on the RHS
Date   Fri, 5 Mar 2010 14:14:45 -0500

Sebastian van Baal <s.vanbaal@arcor.de> :
This seems likely to be problematic no matter what you do--typically
the objective function should be differentiable in the parameters in
these kinds of problems.  What is the theory that drives this
specification?  Is there an alternative parameterization that is
differentiable?

On Fri, Mar 5, 2010 at 10:51 AM, Sebastian van Baal <s.vanbaal@arcor.de> wrote:
> Dear Stata Users:
>
> I attempt to fit a regression model that has a minimum function on the
> right-hand side. My current working solution is to use nonlinear least
> squares:
>
> . nl ( y = {b0} + min({b1}*x1 , {b2}*x2) )
>
> Being admittedly unexperienced with nonlinear least squares, I am unsure if
> this is correct. I have not seen an application of nonlinear least squares
> (or any other form of regression analysis) involving a minimum function.
> Would you say that is the correct way to proceed?
>
> Advance thanks for any hints you can give me.
>
> Sebastian van Baal
> Cologne, Germany
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