Using sklearn I can consider sample weights in my model, like this:
from sklearn.linear_model import LogisticRegression
logreg = LogisticRegression(solver='liblinear')
logreg.fit(X_train, y_train, sample_weight=w_train)
Is there some clever way to consider sample weights also in the Logit method of statsmodel.api?
import statsmodels.api as sm
logit = sm.Logit(y, X)