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Produktbild: Introduction to Multiple Time Series Analysis

Introduction to Multiple Time Series Analysis

49,99 €

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

13.08.1993

Abbildungen

XXI, 545 p.

Verlag

Springer Berlin

Seitenzahl

545

Maße (L/B/H)

24,2/17/3,1 cm

Gewicht

959 g

Auflage

2nd ed. 1993

Sprache

Englisch

ISBN

978-3-540-56940-4

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

13.08.1993

Abbildungen

XXI, 545 p.

Verlag

Springer Berlin

Seitenzahl

545

Maße (L/B/H)

24,2/17/3,1 cm

Gewicht

959 g

Auflage

2nd ed. 1993

Sprache

Englisch

ISBN

978-3-540-56940-4

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: Introduction to Multiple Time Series Analysis
  • 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.- 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.- A.1 Basic Definitions.- A.2 Basic Matrix Operations.- A.3 The Determinant.- A.4 The Inverse, the Adjoint, and Generalized Inverses.- A.4.1 Inverse and Adjoint of a Square Matrix.- A.4.2 Generalized Inverses.- A.5 The Rank.- A.6 Eigenvalues and -vectors — Characteristic Values and Vectors.- A.7 The Trace.- A.8 Some Special Matrices and Vectors.- A.8.1 Idempotent and Nilpotent Matrices.- A.8.2 Orthogonal Matrices and Vectors.- A.8.3 Definite Matrices and Quadratic Forms.- A.9 Decomposition and Diagonalization of Matrices.- A.9.1 The Jordan Canonical Form.- A.9.2 Decomposition of Symmetric Matrices.- A.9.3 The Choleski Decomposition of a Positive Definite Matrix.- A.10 Partitioned Matrices.- A.11 The Kronecker Product.- A.12 The vec and vech Operators and Related Matrices.- A.12.1 The Operators.-A.12.2 The Elimination, Duplication, and Commutation Matrices.- A.13 Vector and Matrix Differentiation.- A.14 Optimization of Vector Functions.- A.15 Problems.- Appendix B. Multivariate Normal and Related Distributions.- B.1 Multivariate Normal Distributions.- B.2 Related Distributions.- Appendix C. Convergence of Sequences of Random Variables and Asymptotic Distributions.- C.1 Concepts of Stochastic Convergence.- C.2 Asymptotic Properties of Estimators and Test Statistics.- C.3 Infinite Sums of Random Variables.- C.4 Maximum Likelihood Estimation.- C.5 Likelihood Ratio, Lagrange Multiplier, and Wald Tests.- Appendix D. Evaluating Properties of Estimators and Test Statistics by Simulation and Resampling Techniques.- D.1 Simulating a Multiple Time Series with VAR Generation Process.- D.2 Evaluating Distributions of Functions of Multiple Time Series by Simulation.- D.3 Evaluating Distributions of Functions of Multiple Time Series by Resampling.- Appendix E. Data Used for Examples and Exercises.- References.- List of Propositions and Definitions.- Index of Notation.- Author Index.