Forecasting and Analytics with the Augmented Dynamic Adaptive Model

ADAM

Ivan Svetunkov (Lancaster University, U.K.)

$194

Hardback

Not in-store but you can order this
How long will it take?

Availability Information

We source books from suppliers in Australia and overseas. For books we don't currently have in stock, the time it takes to get them from our suppliers can vary widely - from a few days to a few months - so we check each book with each supplier to determine the expected time it will take to be supplied to us.

We then advise you accordingly. If the time taken to get any book is too long for you, you can let us know and we will cancel or adjust your order, and refund as required.

To find out the anticipated arrival time for specific items prior to ordering, please contact us by phone or email:

Phone +61 2 9264 3111, or 1800 4 BOOKS (1800 4 26657) if outside Sydney:
option 1 Abbey's Bookshop (Crime, History, Science, Kids & more) • info@abbeys.com.au
option 2 Language Book Centre (ESL & Foreign Languages) • language@abbeys.com.au
option 3 Galaxy Bookshop (Sci-fi, Fantasy, Romance, Graphic Novels) • sf@galaxybooks.com.au

QTY:

English

Chapman & Hall/CRC
17 November 2023

Economic statistics; Probability & statistics; Mathematical & statistical software

Forecasting and Analytics with the Augmented Dynamic Adaptive Model (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, explaining how a variety of instruments can be used to solve real life problems. At the moment, there is no other tool in R or Python that would be able to model both intermittent and regular demand, would support both ETS and ARIMA, work with explanatory variables, be able to deal with multiple seasonalities (e.g. for hourly demand data) and have a support for automatic selection of orders, components and variables and provide tools for diagnostics and further improvement of the estimated model. ADAM can do all of that in one and the same framework. Given the rising interest in forecasting, ADAM, being able to do all those things, is a useful tool for data scientists, business analysts and machine learning experts who work with time series, as well as any researchers working in the area of dynamic models.

Key Features:

• It covers basics of forecasting,

• It discusses ETS and ARIMA models,

• It has chapters on extensions of ETS and ARIMA, including how to use explanatory variables and how to capture multiple frequencies,

• It discusses intermittent demand and scale models for ETS, ARIMA and regression,

• It covers diagnostics tools for ADAM and how to produce forecasts with it,

• It does all of that with examples in R.

By: Ivan Svetunkov (Lancaster University U.K.)
Imprint: Chapman & Hall/CRC
Country of Publication: United Kingdom
Dimensions: Height: 234mm, Width: 156mm,
Weight: 1.070kg
ISBN: 9781032590370
ISBN 10: 1032590378
Pages: 466
Publication Date: 17 November 2023
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

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.