Models for dependent time series / Granville Tunnicliffe Wilson, Marco Reale, John Haywood.
Material type:
TextSeries: Monographs on statistics and applied probability ; 142.Publication details: Boca Raton : CRC Press, ©2016.Description: xv, 323 p. : illustrations ; 24 cmISBN: - 9781584886501 (hardcover : alk. paper)
- 000SA.3 23 T926
| Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|
| Books | ISI Library, Kolkata | 000SA.3 T926 (Browse shelf(Opens below)) | Available | 136934 |
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| 000SA.3 SC355 Stochastic analysis of scaling time series : | 000SA.3 Sh562 Time series analysis and its applications : with R examples / | 000SA.3 T161 Time series analysis : | 000SA.3 T926 Models for dependent time series / | 000SA.3 T939 Non-linear time series : | 000SA.3 W415 Multivariate time series analysis and applications/ | 000SA.3=4 B815 Series cicliche ed osoillanti |
Includes bibliographical references and indexes.
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;
References;
indexes.
The book shows 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.
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