1st Edition
Forecasting and Analytics with the Augmented Dynamic Adaptive Model (ADAM)
1. Introduction
2. Forecasts evaluation
3. Time series components and simple forecasting methods
4. Introduction to ETS
5. Pure additive ADAM ETS
6. Pure multiplicative ADAM ETS
7. General ADAM ETS model
8. Introduction to ARIMA
9. ADAM ARIMA
10. Explanatory variables in ADAM
11. Estimation of ADAM
12. Multiple frequencies in ADAM
13. Intermittent State Space Model
14. Model diagnostics
15. Model selection and combinations in ADAM
16. Handling uncertainty in ADAM
17. Scale model for ADAM
18. Forecasting with ADAM
19. Forecasting functions of the smooth package
20. What’s next?
Biography
Ivan Svetunkov is a Lecturer of Marketing Analytics at Lancaster University, UK and a Marketing Director of Centre for Marketing Analytics and Forecasting. He has PhD in Management Science from Lancaster University and a candidate degree in economics from Saint Petersburg State University of Economics and Finance, Russia. His areas of interests includes statistical methods of analytics and forecasting, focusing on demand forecasting in healthcare, supply chain and retail. He is a creator and a maintainer of several forecasting and analytics-related R packages, such as greybox, smooth and legion.
