Problem with nonlinear regression

#1
Hi,

I am trying to do a nonlinear regression with proportional data, but it doesn't work in Minitab. I'm getting the problems:

- "* WARNING * Singular or nearly singular gradient matrix detected at the final iteration; no statistic based on the gradient matrix will be calculated. "

-"* WARNING * Convergence criterion not met: achieved relative-offset = 2,58199."

but I don't really know why. I have 7 different variables and it works with 5 of them but with the last 2 it doesn't. Any idea what to do? The last 2 variables have a lot of 0 in them since they are not used as often but it should not matter.
 
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#2
It depends on the nonlinear equation that you are using. Some equations cannot handle non-positive (i.e., 0) data.
 

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#4
Ok. Technically, polynomials are still linear regression, so my comment does not apply. I would need to see your analysis.

Can you attach your Minitab project file? I can open version 18, so if you are on 19 or 20, you will need to save it as version 18.
 

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#6
Try "Save Project As" then look at the drop down list under "Save As type:". It should give you the option to save it as a version 18 MPJ file.

If you are on version 19, try updating to the most recent version 19. When Minitab first released 19, they omitted the ability to save as an older version. There was a huge outcry from their customers, so they put it back in.
 
#7
I only got MPX as an alternative, but I think it works now. I changed the part after "Minitab." to MPJ and it seems like it made a difference.

If it works, this is a small example of the data we got but same problem occur. Our problem is with variable 4 and 5. Hopefully it works
 

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#8
No. Even with the MPJ extension, I got an unsupported file format error.

You can attach the raw data in Excel, and copy paste your model into Word.
 

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#10
Sorry for the delay in responding. You are apparently using a new feature in Minitab that is not available in Minitab 18. What made you decide to use a nonlinear approach? The data are extremely noisy to the point that it is impossible to see any real relationship.

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