Time Series Forecasting Part 2 - ARIMA Modeling and Tests
Go to main | Course Page
Section 1: Introduction to ARIMA modeling
- Download Resources
- What is ARIMA Modeling?
Section 2: Stationarity tests
- Why make the series Stationary?
- How to find the order of differencing (d) in ARIMA model
- Understanding Augmented Dickey Fuller Test (ADF Test)
- How to determine number of differencing required to make the time series
stationary?
Section 3: AR and MA Modelling
- Understanding Formula behind AR and MA Model
- Find the order of AR Term (p)
- Find the order of MA Term (p)
- Course Review
Section 4: Build and Tune ARIMA
- Building the ARIMA Model
- How to find the optimal ARIMA Model manually using Out-of-Time Cross
Validation?
- Accuracy Metrics of Time Series Forecast
Section 5: How AutoARIMA works?
- How to do Auto ARIMA Forecast in Python?
- How to interpret residual plots in ARIMA Model?
Section 4: SARIMA and SARIMAX
- How to build SARIMAX Model with exogenous variable?
- How to automatically build SARIMA Model in Python