Introduction to Multiple Time Series Analysis
Published on 31. July 1991
Book
Paperback/Softback
XXI, 546 pages
978-3-540-53194-4 (ISBN)
Description
This graduate-level textbook deals with analyzing and forecasting multiple time series. It considers a wide range of multiple time series models and methods. The models include vector autoregressive, vector autoregressive moving average, cointegrated and periodic processes as well as state space and dynamic simultaneous equations models. Least squares, maximum likelihood and Bayesian methods are considered for estimating these models. Different procedures for model selection or specification are treated and a range of tests and criteria for evaluating the adequacy of a chosen model are introduced. The choice of point and interval forecasts as well as innovation accounting are presented as tools for structural analysis within the multiple time series context.
More details
Language
English
Place of publication
Heidelberg
Germany
Publishing group
Springer Berlin
Target group
College/higher education
Product notice
Paperback (UK-trade)
Illustrations
2 s/w Abbildungen
34figs.
Dimensions
Height: 24.2 cm
Width: 17 cm
Weight
950 gr
ISBN-13
978-3-540-53194-4 (9783540531944)
DOI
10.1007/978-3-662-02691-5
Schweitzer Classification
Other editions
New editions
Helmut Lütkepohl
Introduction to Multiple Time Series Analysis
Book
08/1993
2nd Edition
Springer
€53.49
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Additional editions
Helmut Lütkepohl
Introduction to Multiple Time Series Analysis
E-Book
04/2013
Springer
€85.59
Available for download
Content
1. Introduction.- I. Finite Order Vector Autoregressive Processes.- 2. Stable Vector Autoregressive Processes.- 3. Estimation of Vector Autoregressive Processes.- 4. VAR Order Selection and Checking the Model Adequacy.- 5. VAR Processes with Parameter Constraints.- II. Infinite Order Vector Autoregressive Processes.- 6. Vector Autoregressive Moving Average Processes.- 7. Estimation of VARMA Models.- 8. Specification and Checking the Adequacy of VARMA Models.- 9. Fitting Finite Order VAR Models to Infinite Order Processes.- III. Systems with Exogenous Variables and Nonstationary Processes.- 10. Systems of Dynamic Simultaneous Equations.- 11. Nonstationary Systems with Integrated and Cointegrated Variables.- 12. Periodic VAR Processes and Intervention Models.- 13. State Space Models.- Appendices.- Appendix A. Vectors and Matrices.- Appendix B. Multivariate Normal and Related Distributions.- Appendix C. Convergence of Sequences of Random Variables and Asymptotic Distributions.- Appendix D. Evaluating Properties of Estimators and Test Statistics by Simulation and Resampling Techniques.- Appendix E. Data Used for Examples and Exercises.- References.- List of Propositions and Definitions.- Index of Notation.- Author Index.