Applied Bayesian Forecasting and Time Series Analysis

Name: Applied Bayesian Forecasting and Time Series Analysis
Price: 33.0 USD
Availability: InStock
ISBN: 9780412044014

ISBN-10: 0412044013

ISBN-13: 9780412044014

Edition: 1994

Authors: Andy Pole, Mike West, Jeff Harrison

List price: $200.00

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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…

Book details

List price: $200.00
Copyright year: 1994
Publisher: CRC Press LLC
Publication date: 9/1/1994
Binding: Hardcover
Pages: 430
Size: 6.00" wide x 9.25" long x 1.25" tall
Weight: 1.738

Andrew Pole is a Managing Director at TIG Advisors, LLC, a registered investment advisor in New York. He specializes in quantitative trading strategies and risk management. This book is the result of his own research and experience running a statistical arbitrage hedge fund for eight years. Pole is also the coauthor of Applied Bayesian Forecasting and Time Series Analysis.



Dynamic Bayesian Modelling Theory and Applications


Practical Modelling and Forecasting


Methodological Framework


Analysis of the DLM


Review of Distribution Theory


Classical Time Series Models


Application: Turkey Chick Sales


Application: Market Share


Application: Marriages in Greece


Further Examples and Exercises


Interactive Time Series Analysis and Forecasting


Installing BATS


Tutorial: Introduction to BATS


Files and Directories


Tutorial: Introduction to Modelling


Data