Convergence Failure with Newton, Bug in discrete GLM Poisson model
Bug #673197 reported by
Hanno Starling
This bug affects 1 person
Affects | Status | Importance | Assigned to | Milestone | |
---|---|---|---|---|---|
statsmodels |
New
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Undecided
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Unassigned |
Bug Description
updated diagnosis:
Newton, the default optimizer, does not converge to the correct solution. I didn't look at the details but I guess the stepsize selection is not robust. The gradient in the example is very large. The example converges with Nelder-Mead.
original description:
The attachment has three columns with discrete data. Try scikits.
The residuals of the middle column will all be negative, which is wrong.
This is because the slope is very close to zero which causes some bug in the algorithm.
The first and last column give good results.
summary: |
- Bug in discrete GLM Poisson model + Convergence Failure with Newton, Bug in discrete GLM Poisson model |
description: | updated |
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Hi Hanno
Thanks for the report. Can you add the example or the code that shows the bug? For example, it's not clear to me what is the endogenous variable and which are the regressors, exog.
Trying some combination of columns, I'm not able to get an error. We fixed a 0*log(0) error a while ago in trunk, maybe you see this problem. Are you using 0.2.0. ?