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Models for dependent time series / Granville Tunnicliffe-Wilson, Department of Mathematics and Statistics, Lancaster University, UK; Marco Reale, School of Mathematics and Statistics, University of Canterbury, New Zealand; John Haywood, School of Mathematics and Statistics, Victoria University of Wellington, New Zealand.

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Format:
Book
Author/Creator:
Tunnicliffe-Wilson, Granville, author.
Reale, Marco, author.
Haywood, John (Mathematics professor), author.
Series:
Monographs on statistics and applied probability (Series) ; Volume 142.
Monographs on Statistics and Applied Probability ; Volume 142
Language:
English
Subjects (All):
Time-series analysis.
Autoregression (Statistics).
Mathematical statistics.
Physical Description:
1 online resource (320 p.)
Edition:
1st ed.
Place of Publication:
Boca Raton : CRC Press, 2015.
Language Note:
English
Summary:
Models for Dependent Time Series addresses the issues that arise and the methodology that can be applied when the dependence between time series is described and modeled. Whether you work in the economic, physical, or life sciences, the book shows you how to draw meaningful, applicable, and statistically valid conclusions from multivariate (or vector) time series data.The first four chapters discuss the two main pillars of the subject that have been developed over the last 60 years: vector autoregressive modeling and multivariate spectral analysis. These chapters provide the foundational mater
Contents:
""Cover""; ""Contents""; ""Preface""; ""Chapter 1: Introduction and overview""; ""Chapter 2: Lagged regression and autoregressive models""; ""Chapter 3: Spectral analysis of dependent series""; ""Chapter 4: Estimation of vector autoregressions""; ""Chapter 5: Graphical modeling of structural VARs""; ""Chapter 6: VZAR: An extension of the VAR model""; ""Chapter 7: Continuous time VZAR models""; ""Chapter 8: Irregularly sampled series""; ""Chapter 9: Linking graphical, spectral and VZAR methods""; ""References""
Notes:
A Chapman & Hall book.
Includes bibliographical references.
Description based on print version record.
ISBN:
9781040208427
1040208428
9780429144400
0429144407
9781420011500
1420011502
OCLC:
916953896

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