ARIMA and Prophet: Time Series Forecasting

This lesson covers two powerful forecasting approaches: classical ARIMA models and Facebook's Prophet for automated forecasting.

ARIMA Model

ARIMA Implementation

The ARIMA(p,d,q) model:

where = AR order, = differencing order, = MA order.

SARIMA (Seasonal ARIMA)

SARIMA extends ARIMA with seasonal components :

Prophet Implementation

Model Evaluation

Diagnostics

Key Takeaways

1. Use auto_arima to find optimal (p,d,q) parameters
2. SARIMA handles seasonal patterns with (P,D,Q,s)
3. Prophet is more robust to missing data and outliers
4. Always check residuals for white noise
5. Compare multiple models using MAPE, RMSE, and MASE