Details

Subject(s)

• Autoregression (Statistics) [Browse]
• Linear models (Statistics) [Browse]

Series

Springer series in statistics. Probability and its applications [More in this series]

Summary note

During the last two decades, considerable progress has been made in statistical time series analysis. The aim of this book is to present a survey of one of the most active areas in this field: the identification of autoregressive moving-average models, i.e., determining their orders. Readers are assumed to have already taken one course on time series analysis as might be offered in a graduate course, but otherwise this account is self-contained. The main topics covered include: Box-Jenkins' method, inverse autocorrelation functions, penalty function identification such as AIC, BIC techniques and Hannan and Quinn's method, instrumental regression, and a range of pattern identification methods. Rather than cover all the methods in detail, the emphasis is on exploring the fundamental ideas underlying them. Extensive references are given to the research literature and as a result, all those engaged in research in this subject will find this an invaluable aid to their work.

Bibliographic references

Includes bibliographical references (p. 149-196) and index.

Action note

Committed to retain in perpetuity — ReCAP Shared Collection (HUL)

Contents

• 1. Introduction
• 1.1. ARMA Model
• 1.2. History
• 1.3. Algorithms
• 1.4. Estimation
• 1.5. Nonstationary Processes
• 1.6. Additional References
• 2. The Autocorrelation Methods
• 2.1. Box and Jenkins' Method
• 2.2. The Inverse Autocorrelation Method
• 2.3. Additional References
• 3. Penalty Function Methods
• 3.1. The Final Prediction Error Method
• 3.2. Akaike's Information Criterion
• 3.3. Generalizations
• 3.4. Parzen's Method
• 3.5. The Bayesian Information Criterion
• 3.6. Hannan and Quinn's Criterion
• 3.7. Consistency
• 3.8. Some Relations
• 3.9. Additional References
• 4. Innovation Regression Methods
• 4.1. AR and MA Approximations
• 4.2. Hannan and Rissanen's Method
• 4.3. Koreisha and Pukkila's Method
• 4.4. The KL Spectral Density
• 4.5. Additional References
• 5. Pattern Identification Methods
• 5.1. The 3-Pattern Method
• 5.2. The R and S Array Method
• 5.3. The Corner Method
• 5.4. The GPAC Methods
• 5.5. The ESACF Method
• 5.6. The SCAN Method
• 5.7. Woodside's Method
• 5.8. Three Systems of Equations
• 5.9. Additional References
• 6. Testing Hypothesis Methods
• 6.1. Three Asymptotic Test Procedures
• 6.2. Some Test Statistics
• 6.3. The Portmanteau Statistic
• 6.4. Sequential Testing Procedures
• 6.5. Additional References.

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ISBN

• 0387977953 (New YorK)
• 3540977953 (Berlin)

LCCN

^^^91045681^

OCLC

25130694

RCP

H - S

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