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From |
Richard Williams <Richard.A.Williams.5@ND.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
RE: st: Nonlinear regression and constraints |

Date |
Wed, 29 Jun 2005 02:18:13 -0500 |

At 11:49 PM 6/28/2005 -0700, Daniel Schneider wrote:

If the estimated parameters are both below 0 - and 0 is the lowest value allowable - then isn't the simplest way to impose the constraints you want is to just drop those variables from the equation??? (That is the simplest way I know of to constrain effects to be 0.)Without going to much into detail: my parameters are percentages. They can only range from 0 to 1. There may be a better solution (i.e. a solution that better fits the data) beyond 1, BUT, as I said, by definition they cannot be above 1 (or below 0). So the best solution that is possible has to be between 0 and 1. My current model gives me values which are both below 0 (I changed the equation a little bit, corrected a minor error, but that doesn't matter for the problem).

I suspect that idea isn't very appealing to you. But, if you are getting "impossible" results, I suspect you've also got some problems with your model specification or your theory or your data. You may want to think some more about your basic approach before worrying too much about nailing the constraints.

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Richard Williams, Notre Dame Dept of Sociology

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**References**:**RE: st: Nonlinear regression and constraints***From:*Richard Williams <Richard.A.Williams.5@ND.edu>

**RE: st: Nonlinear regression and constraints***From:*"Daniel Schneider" <daniel.schneider@stanford.edu>

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