M5 - ARIMA Models

Learning Objectives

The learning goals for this module are:

• Discuss the non-seasonal ARIMA class of models for stationary series and its variations (AR, MA and ARMA);
  
• Understand the main differences between autoregressive and moving average component;
  
• Understand the unit root condition for stationarity;
  
• Learn how to fit non-seasonal ARIMA models in R.
  

Slides

Here is a link to the slide deck used in class.

Resources

• Tutorial on Time Series Modeling

• Time Series Analysis with Applications - Cryer and Shan - Chapter 4: Models for Stationary Time Series
  

• Forecasting: Principles and Practice by Rob J Hyndman and George Athanasopoulos, Chapter 8: ARIMA Models

Recordings (optional)

Here you will also find some helpful recordings.

• Intro to ARIMA Models - Part 1
  
• Intro to ARIMA Models - Part 2
  
• How to fit ARIMA models in R - Part 1
  
• How to fit ARIMA models in R - Part 2

Deliverables

For this module you will complete Assignment 6. The due date for A6 is February 28.