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Introduction to multiple time series analysis

Author: Helmut Lütkepohl
Publisher: Berlin ; New York : Springer-Verlag, ©1993.
Edition/Format:   Print book : English : 2nd edView all editions and formats
Summary:

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,  Read more...

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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Helmut Lütkepohl
ISBN: 3540569405 9783540569404 0387569405 9780387569406
OCLC Number: 28507731
Description: xxi, 545 pages : illustrations ; 25 cm
Contents: Ch. 1. Introduction --
1.1. Objectives of Analyzing Multiple Time Series --
1.2. Some Basics --
1.3. Vector Autoregressive Processes --
1.4. Outline of the Following Chapters --
Ch. 2. Stable Vector Autoregressive Processes --
2.1. Basic Assumptions and Properties of VAR Processes --
2.2. Forecasting --
2.3. Structural Analysis with VAR Models --
Ch. 3. Estimation of Vector Autoregressive Processes --
3.2. Multivariate Least Squares Estimation --
3.3. Least Squares Estimation with Mean-Adjusted Data and Yule-Walker Estimation --
3.4. Maximum Likelihood Estimation --
3.5. Forecasting with Estimated Processes --
3.6. Testing for Granger-Causality and Instantaneous Causality --
3.7. The Asymptotic Distributions of Impulse Responses and Forecast Error Variance Decompositions --
Ch. 4. VAR Order Selection and Checking the Model Adequacy --
4.2. A Sequence of Tests for Determining the VAR Order --
4.3. Criteria for VAR Order Selection --
4.4. Checking the Whiteness of the Residuals --
4.5. Testing for Nonnormality --
4.6. Tests for Structural Change --
Ch. 5. VAR Processes with Parameter Constraints --
5.2. Linear Constraints --
5.3. VAR Processes with Nonlinear Parameter Restrictions --
5.4. Bayesian Estimation --
Ch. 6. Vector Autoregressive Moving Average Processes --
6.2. Finite Order Moving Average Processes --
6.3. VARMA Processes --
6.4. The Autocovariances and Autocorrelations of a VARMA(p, q) Process --
6.5. Forecasting VARMA Processes --
6.6. Transforming and Aggregating VARMA Processes --
6.7. Interpretation of VARMA Models --
Ch. 7. Estimation of VARMA Models --
7.1. The Identification Problem --
7.2. The Gaussian Likelihood Function --
7.3. Computation of the ML Estimates --
7.4. Asymptotic Properties of the ML Estimators --
7.5. Forecasting Estimated VARMA Processes --
7.6. Estimated Impulse Responses --
Ch. 8. Specification and Checking the Adequacy of VARMA Models --
8.2. Specification of the Final Equations Form --
8.3. Specification of Echelon Forms --
8.4. Remarks on other Specification Strategies for VARMA Models --
8.5. Model Checking --
8.6. Critique of VARMA Model Fitting --
Ch. 9. Fitting Finite Order VAR Models to Infinite Order Processes --
9.2. Multivariate Least Squares Estimation --
9.3. Forecasting --
9.4. Impulse Response Analysis and Forecast Error Variance Decompositions --
Ch. 10. Systems of Dynamic Simultaneous Equations --
10.2. Systems with Exogenous Variables --
10.3. Estimation --
10.4. Remarks on Model Specification and Model Checking --
10.5. Forecasting --
10.6. Multiplier Analysis --
10.7. Optimal Control --
10.8. Concluding Remarks on Dynamic SEMs --
Ch. 11. Nonstationary Systems with Integrated and Cointegrated Variables --
11.2. Estimation of Integrated and Cointegrated VAR(p) Processes --
11.3. Forecasting and Structural Analysis --
11.4. Model Selection and Model Checking --
Ch. 12. Periodic VAR Processes and Intervention Models --
12.2. The VAR(p) Model with Time Varying Coefficients --
12.3. Periodic Processes --
12.4. Intervention Models --
Ch. 13. State Space Models --
13.2. State Space Models --
13.3. The Kalman Filter --
13.4. Maximum Likelihood Estimation of State Space Models --
13.5. A Real Data Example --
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.
Responsibility: Helmut Lütkepohl.
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