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- Adding Constraints to Coefficients in Regression Models

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Aug 26, 2015 12:23 PM
(4178 views)

I am working on a market mix model and the impact of promotions on sales. I would expect the coefficients to be positive or 0, but some of the models are producing negative coefficients.

Is there a way to add a constraint to the coefficients of some variables to force them to be positive?

Thanks!

Paul

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Paul, you can use the Parameter Bounds pulldown in the Nonlinear platform, specify the bounds you wish, and then iteratively fit a linear model.

The Nonlinear platform will make you specify a model in the Formula Editor and supply some Initial Values for the parameters. You won't enjoy some of the model diagnostics you might be using in another platform (R^2, for instance, is not provided for nonlinear models), but at least you can constrain the parameters appropriately and (if your model converges) get a hopefully useful answer.

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Paul, you can use the Parameter Bounds pulldown in the Nonlinear platform, specify the bounds you wish, and then iteratively fit a linear model.

The Nonlinear platform will make you specify a model in the Formula Editor and supply some Initial Values for the parameters. You won't enjoy some of the model diagnostics you might be using in another platform (R^2, for instance, is not provided for nonlinear models), but at least you can constrain the parameters appropriately and (if your model converges) get a hopefully useful answer.

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Aug 27, 2015 9:39 AM
(3928 views)
| Posted in reply to message from Kevin_Anderson 08/26/2015 04:51 PM

Thanks. This worked perfectly.