Springer Series in Statistics

ARMA Model Identification

Authors: Choi, ByoungSeon

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About this book

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.

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Buy this book

eBook $89.99 net
( price for USA )
  • ISBN 978-1-4613-9745-8
  • digitally watermarked, no DRM
  • included format: PDF
  • eBooks can be used on all Reading Devices
Softcover $119.00 net
( price for USA )
  • ISBN 978-1-4613-9747-2
  • free shipping for individuals worldwide
  • usually dispatched within 3 to 5 business days

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Bibliographic Information

Bibliographic Information
Book Title
ARMA Model Identification
Series Title
Springer Series in Statistics
Copyright
1992
Publisher
Springer-Verlag New York
Copyright Holder
Applied Probability Trust
eBook ISBN
978-1-4613-9745-8
DOI
10.1007/978-1-4613-9745-8
Softcover ISBN
978-1-4613-9747-2
Series ISSN
0172-7397
Edition Number
1
Topics