Applied Bayesian Forecasting and Time Series Analysis

Series:
Chapman & Hall/CRC Texts in Statistical Science
Published:
September 01, 1994 by Chapman and Hall/CRC - 432 Pages
Author(s):
Andy Pole, MD Invictus Partners, USA; Mike West, Duke University, Durham, North Carolina, USA; Jeff Harrison, Cumbria, England, UK

Purchasing Options

Hardback
$145.95
Add to cart
ISBN 9780412044014
Cat# C4401
 

Features

  • Incorporates a complete theoretical development of the DLM, illustrating each step through analysis of real time series data
  • Integrates the BATS computer program, which provides all of the modeling facilities discussed in the book
  • Provides hands-on time series analysis and forecasting experience
  • Includes more than 50 data sets-available online atwww.crcpress.com/e_products/downloads- studied as applications, presented with preliminary analysis for exercises, or provided for further exploration

    • Summary

    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.

    • Table of Contents

    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
    Tutorial: Tutorial: Advanced Modelling
    Tutorial: Modelling with Incomplete Data
    Tutorial: Data Management
    BATS REFERENCE
    Communications
    Menu Descriptions

    Editorial Reviews

    "This book has filled a significant gap in the market for statistical texts. It should move Bayesian techniques for time series analysis and forecasting into the standard repertoire of applied statisticians. I think that it is an excellent book, and recommend it, especially to those who are not already familiar with these ideas."
    -The Statistician

    Downloads Updates


    Resource OS Platform Updated Description Instructions
    C4401.zip All Windows Version December 09, 2003

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