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- Keeping JMP model predictions positive?

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Jun 15, 2012 8:41 AM
(1045 views)

4 REPLIES

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Jun 15, 2012 9:11 AM
(904 views)

As far as I know, there is no capability in JMP to fit a linear model and force the predictions to be positive. However, the general question you ask is not really a JMP question but a modeling question.

I believe that one solution here is to fit a non-linear model to your data. If you choose the right non-linear model, the predictions will be forced to be positive. Another solution might be to transform your data somehow, fit the model, and then un-transform (again, if you do this properly you can force the predictions to be positive). What the right non-linear model is, and/or what the right transformation is, depends on your data.

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Jun 15, 2012 1:16 PM
(904 views)

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Jun 15, 2012 1:26 PM
(904 views)

Ah, terminology. When a statistician (such as me) speaks about a non-linear model, that term non-linear is guaranteed to confuse anyone who isn't a statistician. Sorry about that.

Your quadratic model (factorial to degree 2) is considered a "linear" model in this terminology, even though it has squared terms and interactions and the result isn't a straight line.

What I meant by non-linear was something like an exponential, or a piece-wise fit, or anything other than a polynomial, which is what JMP fits in Fit Model.

The above isn't really relevant to solving the problem, but it might be in the future. So, where does that leave us? I think you need to decide if you need a good fit near a response value of zero, where you are having trouble, or a good fit elsewhere, or both. Is the goal of this modeling to predict near a response of zero? Also, when you use the profiler and get a time of –45, this could be indicating you are trying to predict in an infeasible area, or an area where the model doesn't apply. Lastly, I remain concerned that you claim you get a r-sq close to 1 (what does "close" mean?) and yet the profiler is giving you negative predictions. Are you dragging the profiler sliders beyond the range of the x data?

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Jun 18, 2012 4:36 AM
(904 views)

You could try taking a log transform of the response variable

Dave

-Dave