Applied Bayesian Forecasting and Time Series Analysis
- Publisher's listprice GBP 61.99
-
29 615 Ft (28 205 Ft + 5% VAT)
The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.
- Discount 20% (cc. 5 923 Ft off)
- Discounted price 23 692 Ft (22 564 Ft + 5% VAT)
Subcribe now and take benefit of a favourable price.
Subscribe
29 615 Ft
Availability
Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
Not in stock at Prospero.
Why don't you give exact delivery time?
Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Edition number 1
- Publisher Chapman and Hall
- Date of Publication 2 December 2019
- ISBN 9780367449384
- Binding Paperback
- No. of pages432 pages
- Size 234x156 mm
- Weight 453 g
- Language English 17
Categories
Short description:
This book is about practical forecasting and analysis of time series. It describes how to analyse time series data, how to identify structure, how to explain observed behaviour, how to model structures and behaviours, and how to use insight gained from the analysis to make informed forecasts.
MoreLong description:
Practical in its approach, Applied Bayesian Forecasting and Time Series Analysis provides the theories, methods, and tools necessary for forecasting and the analysis of time series. The authors unify the concepts, model forms, and modeling requirements within the framework of the dynamic linear mode (DLM). They include a complete theoretical development of the DLM and illustrate each step with analysis of time series data. Using real data sets the authors: Explore diverse aspects of time series, including how to identify, structure, explain observed behavior, model structures and behaviors, and interpret analyses to make informed forecasts Illustrate concepts such as component decomposition, fundamental model forms including trends and cycles, and practical modeling requirements for routine change and unusual events Conduct all analyses in the BATS computer programs, furnishing online that program and the more than 50 data sets used in the text The result is a clear presentation of the Bayesian paradigm: quantified subjective judgements derived from selected models applied to time series observations. Accessible to undergraduates, this unique volume also offers complete guidelines valuable to researchers, practitioners, and advanced students in statistics, operations research, and engineering.
MoreTable of Contents:
Part A: Dynamic Bayesian Modelling Theory and Applications 1. Practical Modelling and Forecasting 2. Methodological Framework 3. Analysis of the DLM 4. Application: Turkey Chick Sales 5. Application: Market Share 6. Application: Marriages in Greece 7. Further Examples and Exercises Part B: Interactive Time Series Analysis and Forecasting 8. Installing BATS 9. Tutorials Introduction to BATS 10. Tutorial: Introduction to Modelling 11. Tutorial: Advanced Modelling 12. Tutorial: Modelling with Incomplete Data 13. Tutorial: Data Management Part C: Bats Reference 14. Communications 15. Menu Descriptions
More
