How can I implement robust regression in Python?

How can I implement robust regression in Python?

You can use libraries like statsmodels or scikit-learn. Would you like a code example?

Yes, please provide a code example using statsmodels.

Sure! Here's a simple example:

import statsmodels.api as sm
import numpy as np

# Sample data
X = np.random.rand(100, 1)
Y = 2 * X.squeeze() + np.random.normal(size=100)

# Adding a constant for the intercept
X = sm.add_constant(X)

# Fit a robust regression model
model = sm.RLM(Y, X).fit()
print(model.summary())

What are the advantages of using robust regression?

Robust regression is less sensitive to outliers and can provide more reliable estimates when data is contaminated.