Skip to content
You are not logged in |Login  
     
Limit search to available items
Record:   Prev Next
Resources
More Information
Bestseller
BestsellerE-book
Author Tunnicliffe-Wilson, Granville, author.

Title Models for dependent time series / Granville Tunnicliffe-Wilson, Marco Reale, John Haywood.

Publication Info. Boca Raton : CRC Press LLC, [2015]
©2015

Item Status

Description 1 online resource (xv, 302 pages) : illustrations.
Physical Medium polychrome
Description text file
Series Monographs on statistics and applied probability (Series) ; 142
Monographs on statistics and applied probability (Series) ; 142.
Bibliography Includes bibliographical references.
Contents 1. Introduction and overview -- 2. Lagged regression and autoregressive models -- 3. Spectral analysis of dependent series -- 4. Estimation of vector autoregressions -- 5. Graphical modeling of structural VARs -- 6. VZAR : an extension of the VAR model -- 7. Continuous time VZAR models -- 8. Irregularly sampled series -- 9. Linking graphical, spectral and VZAR methods.
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 material for the remaining chapters, which cover the construction of structural models and the extension of vector autoregressive modeling to high frequency, continuously recorded, and irregularly sampled series. The final chapter combines these approaches with spectral methods for identifying causal dependence between time series. Web Resource A supplementary website provides the data sets used in the examples as well as documented MATLAB® functions and other code for analyzing the examples and producing the illustrations. The site also offers technical details on the estimation theory and methods and the implementation of the models.
Local Note eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America
Subject Time-series analysis.
Time-series analysis.
Autoregression (Statistics)
Autoregression (Statistics)
Mathematical statistics.
MATHEMATICS -- Applied.
Mathematical statistics.
MATHEMATICS -- Probability & Statistics -- General.
Added Author Reale, Marco, author.
Haywood, John (Mathematics professor), author.
Other Form: Print version: Tunnicliffe-Wilson, Granville. Models for dependent time series. Boca Raton, FL : CRC Press, Taylor & Francis Group, [2016] 9781584886501 (DLC) 2015014849 (OCoLC)144565879
ISBN 9781420011500 (electronic book)
1420011502 (electronic book)
9781584886501 (hardcover alkaline paper)
1584886501 (hardcover alkaline paper)