Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Fitting GLM with a pre-assigned starting parameter #1601

Closed
yizhong opened this issue Apr 18, 2014 · 0 comments
Closed

Fitting GLM with a pre-assigned starting parameter #1601

yizhong opened this issue Apr 18, 2014 · 0 comments

Comments

@yizhong
Copy link

yizhong 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 as completed Apr 18, 2014
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant