Time Series Forecasting Part 2 - ARIMA Modeling and Tests

Go to main | Course Page

Section 1: Introduction to ARIMA modeling

  1. Download Resources
  2. What is ARIMA Modeling?

Section 2: Stationarity tests

  1. Why make the series Stationary?
  2. How to find the order of differencing (d) in ARIMA model
  3. Understanding Augmented Dickey Fuller Test (ADF Test)
  4. How to determine number of differencing required to make the time series stationary?

Section 3: AR and MA Modelling

  1. Understanding Formula behind AR and MA Model
  2. Find the order of AR Term (p)
  3. Find the order of MA Term (p)
  4. Course Review

Section 4: Build and Tune ARIMA

  1. Building the ARIMA Model
  2. How to find the optimal ARIMA Model manually using Out-of-Time Cross Validation?
  3. Accuracy Metrics of Time Series Forecast

Section 5: How AutoARIMA works?

  1. How to do Auto ARIMA Forecast in Python?
  2. How to interpret residual plots in ARIMA Model?

Section 4: SARIMA and SARIMAX

  1. How to build SARIMAX Model with exogenous variable?
  2. How to automatically build SARIMA Model in Python
Report abuse