Chapter 1 - Getting Started
- Notes - Planning & Goals, Basic Steps, Choosing and Fitting Models.
Chapter 2 - Time Series Graphics
- Notes & Exercises -
tsibble objects, Time Plots, Scatterplots, Lag Plots, Autocorrelation.
Chapter 3 - Time Series Decomposition
- Notes & Exercises - Transformations and Adjustments, Time Series Components, Moving Averages, Classical Decomposition; X11, SEATS and STL Decomposition
Chapter 4 - Time Series Features
Chapter 6 - Judgmental Forecasts
- Notes - Limitations, Principles, Delphi Method, Scenario Forecasting, Judgemental Adjustments.
Chapter 7 - Time Series Regression Models
- Notes - Linear, Least Squares, Selecting Predictors, Forecasting with Regression, Martix Formulation, Non-linear Regression.
- Exercises
Chapter 8 - Exponential Smoothing
- Notes - Simple exponential smoothing, Holt’s Method, Holt-Winters Seasonal Method, Innovations State Space Models.
- Exercises
Chapter 9 - ARIMA Models
- Notes - Stationarity and Differencing, Backshift Notation, Autoregressive Models, Moving Average Models, Estimation and Order, Forecasting, Seasonal ARIMA.
Chapter 10 - Dynamic Regression Models
Chapter 11 - Hierarchical and Grouped Series
Chapter 12 - Advances Forecasting Methods
Chapter 13 - Practical Forecasting Issues