Springer Series in Statistics

Elements of Multivariate Time Series Analysis

Authors: Reinsel, Gregory C.

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About this book

In this revised edition, some additional topics have been added to the original version, and certain existing materials have been expanded, in an attempt to pro­ vide a more complete coverage of the topics of time-domain multivariate time series modeling and analysis. The most notable new addition is an entirely new chapter that gives accounts on various topics that arise when exogenous vari­ ables are involved in the model structures, generally through consideration of the so-called ARMAX models; this includes some consideration of multivariate linear regression models with ARMA noise structure for the errors. Some other new material consists of the inclusion of a new Section 2. 6, which introduces state-space forms of the vector ARMA model at an earlier stage so that readers have some exposure to this important concept much sooner than in the first edi­ tion; a new Appendix A2, which provides explicit details concerning the rela­ tionships between the autoregressive (AR) and moving average (MA) parameter coefficient matrices and the corresponding covariance matrices of a vector ARMA process, with descriptions of methods to compute the covariance matrices in terms of the AR and MA parameter matrices; a new Section 5.

Buy this book

Softcover $109.00
price for USA
  • ISBN 978-0-387-40619-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Elements of Multivariate Time Series Analysis
Authors
Series Title
Springer Series in Statistics
Copyright
1997
Publisher
Springer-Verlag New York
Copyright Holder
Springer Science+Business Media New York
Softcover ISBN
978-0-387-40619-0
Series ISSN
0172-7397
Edition Number
2
Number of Pages
XVII, 358
Topics