python import numpy as np import statsmodels.api as sm np.random.seed(0) n = 100 X = np.linspace(0, 10, n) X = sm.add_constant(X) beta = [1, 2] epsilon = np.random.normal(size=n) y = np.dot(X, beta) + epsilon model = sm.OLS(y, X) bayesian_model = model.fit(method='mcmc', cov_type='robust') print(bayesian_model.summary())