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Fitting GLM with a pre-assigned starting parameter #1601

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yizhong opened this issue Apr 18, 2014 · 0 comments

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commented Apr 18, 2014

Hi,

I am using generalized linear model in statsmodels to fit biological data, which follows the Gamma distribution.

My question is can we make glm to allow a pre-assigned starting coefficient?
I know the starting point is calculated by "family.starting_mu()": (y+y.mean())/2,
Could it be useful to have a small change at line 386 in generalized_linear_model.py
https://github.com/statsmodels/statsmodels/blob/master/statsmodels/genmod/generalized_linear_model.py#L386
like this:

if starting_coefficient is Null:
mu = self.family.starting_mu(self.endog)
else:
mu = np.dot(exog, starting_coefficient)

I saw the similar question raised before:
#443 (comment)
But I didn't get the point.

Many thanks,

Yi

@yizhong yizhong closed this Apr 18, 2014

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