Turn on suggestions

Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type.

Showing results for

- JMP User Community
- :
- Discussions
- :
- Discussions
- :
- Adding Constraints to Coefficients in Regression Models

Topic Options

- Subscribe to RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Printer Friendly Page

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Get Direct Link
- Email to a Friend
- Report Inappropriate Content

Aug 26, 2015 12:23 PM
(4484 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

1 ACCEPTED SOLUTION

Accepted Solutions

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Get Direct Link
- Email to a Friend
- Report Inappropriate Content

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.

2 REPLIES

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Get Direct Link
- Email to a Friend
- Report Inappropriate Content

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.

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Get Direct Link
- Email to a Friend
- Report Inappropriate Content

Re: Adding Constraints to Coefficients in Regression Models

Aug 27, 2015 9:39 AM
(4234 views)
| Posted in reply to message from Kevin_Anderson 08/26/2015 04:51 PM

Thanks. This worked perfectly.