Reputation: 607
The question may simple, but I would like to ask question about the result from statsmodel
.
According to the reference, we can get the result from
print(gamma_results.summary())
https://www.statsmodels.org/devel/glm.html
Generalized Linear Model Regression Results
==============================================================================
Dep. Variable: YES No. Observations: 32
Model: GLM Df Residuals: 24
Model Family: Gamma Df Model: 7
Link Function: inverse_power Scale: 0.0035843
Method: IRLS Log-Likelihood: -83.017
Date: Tue, 16 Aug 2022 Deviance: 0.087389
Time: 13:46:12 Pearson chi2: 0.0860
No. Iterations: 6 Pseudo R-squ. (CS): 0.9800
Covariance Type: nonrobust
======================================================================================
coef std err z P>|z| [0.025 0.975]
--------------------------------------------------------------------------------------
const -0.0178 0.011 -1.548 0.122 -0.040 0.005
COUTAX 4.962e-05 1.62e-05 3.060 0.002 1.78e-05 8.14e-05
UNEMPF 0.0020 0.001 3.824 0.000 0.001 0.003
MOR -7.181e-05 2.71e-05 -2.648 0.008 -0.000 -1.87e-05
ACT 0.0001 4.06e-05 2.757 0.006 3.23e-05 0.000
GDP -1.468e-07 1.24e-07 -1.187 0.235 -3.89e-07 9.56e-08
AGE -0.0005 0.000 -2.159 0.031 -0.001 -4.78e-05
COUTAX_FEMALEUNEMP -2.427e-06 7.46e-07 -3.253 0.001 -3.89e-06 -9.65e-07
======================================================================================
Would you tell me what it means No. Iterations:
?
Upvotes: 1
Views: 86
Reputation: 2206
Most of the GLMs do not have an analytical solution, such as the linear regression does.
When you lack an analytical solution you have to use an optimization algorithm to achieve an "optimal" solution.
No. Iterations
is the number of iterations that were needed by the optimization algorithm to reach a good enough solution (given some exit criteria).
Hope this helps!
Upvotes: 2