We will cover the following recipes in this chapter: 

• The general ARIMA model  
• Seasonality and SARIMAX models  
• Choosing the best model with the forecast package  
• Vector autoregressions (VARs)  
• Facebook's automatic Prophet forecasting   
• Modeling count temporal data  
• Imputing missing values in time series  
• Anomaly detection  
• Spectral decomposition of time series