Pca Analysis, Survival Analysis, Python, Finance, Business.
baseline_model.fit(df, distribution="weibull").survive(censoring_time) # Plot results fig, ax = plt.subplots(figsize=(8,6)) ax.step(range(len(df)), baseline_results, color="#7FBBB8") ax.plot([len(df) - int(round((target_return - df[-1][0])/df[-1][1])) + 1, len(df)], [0, 0], 'k--', linewidth=2)