statsmodels.genmod.generalized_linear_model.GLM.fit
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GLM.fit(start_params=None, maxiter=100, method='IRLS', tol=1e-08, scale=None, cov_type='nonrobust', cov_kwds=None, use_t=None, **kwargs)
[source] -
Fits a generalized linear model for a given family.
Parameters: maxiter : int, optional
Default is 100.
method : string
Default is ?IRLS? for iteratively reweighted least squares. This is currently the only method available for GLM fit.
scale : string or float, optional
scale
can be ?X2?, ?dev?, or a float The default value is None, which usesX2
for Gamma, Gaussian, and Inverse Gaussian.X2
is Pearson?s chi-square divided bydf_resid
. The default is 1 for the Binomial and Poisson families.dev
is the deviance divided by df_residtol : float
Convergence tolerance. Default is 1e-8.
start_params : array-like, optional
Initial guess of the solution for the loglikelihood maximization. The default is family-specific and is given by the
family.starting_mu(endog)
. If start_params is given then the initial mean will be calculated asnp.dot(exog, start_params)
.Notes
This method does not take any extra undocumented
kwargs
.
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