Ivan Svetunkov

Forecasting and Analytics with the Augmented Dynamic Adaptive Model (ADAM) (eBook, PDF)

• Format: PDF

Produktbeschreibung

Forecasting and Analytics with ADAM focuses on a time series model in Single Source of Error state space form, called "ADAM" (Augmented Dynamic Adaptive Model). The book demonstrates a holistic view to forecasting and time series analysis using dynamic models to solve real life problems.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 494
• Erscheinungstermin: 17. November 2023
• Englisch
• ISBN-13: 9781000992717
• Artikelnr.: 69011592

Autorenporträt

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.

Inhaltsangabe

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?