GLM - Generalized Linear Models

OLS - Ordinary Least Squares

Python code

import statsmodels.api as sm
sm.OLS.from_formula('y ~ x1 + x2 + x3', data=df).fit().summary()

LOGIT - Logistic Regression

Python code

import statsmodels.api as sm
sm.Logit.from_formula('y ~ x1 + x2 + x3', data=df).fit().summary()

MLogit - Multinomial Logistic Regression

Python code

import statsmodels.api as sm
sm.MNLogit.from_formula('y ~ x1 + x2 + x3', data=df).fit().summary()

Poisson Regression

Python code

import statsmodels.api as sm
sm.Poisson.from_formula('y ~ x1 + x2 + x3', data=df).fit().summary()

Bneg - Negative Binomial Regression

Python code

import statsmodels.api as sm
sm.NegativeBinomial.from_formula('y ~ x1 + x2 + x3', data=df).fit().summary()

ZIP - Zero Inflated Poisson

Python code

import statsmodels.api as sm
sm.ZeroInflatedPoisson.from_formula('y ~ x1 + x2 + x3', data=df).fit().summary()

ZINB - Zero Inflated Negative Binomial

Python code

import statsmodels.api as sm
sm.ZeroInflatedNegativeBinomial.from_formula('y ~ x1 + x2 + x3', data=df).fit().summary()