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

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.