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- Table of contents
- Hamilton, James D. (James Douglas), 1954-
- Princeton, N.J. : Princeton University Press, c1994.
xiv, 799 p. : ill. ; 26 cm.
- Time-series analysis.
- Local subjects:
- Análisis de series de tiempo
- "The last decade has brought dramatic changes in the way that researchers analyze time series data. This much-needed book synthesizes all of the major recent advances and develops a single, coherent presentation of the current state of the art of this increasingly important field. James Hamilton provides for the first time a thorough and detailed textbook account of important innovations such as vector autoregressions, estimation by generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, Hamilton presents traditional tools for analyzing dynamic systems, including linear representations, autocovariance, generating functions, spectral analysis, and the Kalman filter, illustrating their usefulness both for economic theory and for studying and interpreting real-world data." "This book is intended to provide students, researchers, and forecasters with a definitive, self-contained survey of dynamic systems, econometrics, and time series analysis. Starting from first principles, Hamilton's lucid presentation makes both old and new developments accessible to first-year graduate students and nonspecialists. Moreover, the work's thoroughness and depth of coverage will make Time Series Analysis an invaluable reference for researchers at the frontiers of the field. Hamilton achieves these dual objectives by including numerous examples that illustrate exactly how the theoretical results are used and applied in practice, while relegating many details to mathematical appendixes at the end of chapters. As an intellectual roadmap of the field for students and researchers alike, this volume promises to be the authoritative guide for years to come."--BOOK JACKET.
- 1. Difference Equations
2. Lag Operators
3. Stationary ARMA Processes
5. Maximum Likelihood Estimation
6. Spectral Analysis
7. Asymptotic Distribution Theory
8. Linear Regression Models
9. Linear Systems of Simultaneous Equations
10. Covariance-Stationary Vector Processes
11. Vector Autoregressions
12. Bayesian Analysis
13. The Kalman Filter
14. Generalized Method of Moments
15. Models of Nonstationary Time Series
16. Processes with Deterministic Time Trends
17. Univariate Processes with Unit Roots
18. Unit Roots in Multivariate Time Series
20. Full-Information Maximum Likelihood Analysis of Cointegrated Systems
21. Time Series Models of Heteroskedasticity
22. Modeling Time Series with Changes in Regime
D Greek Letters and Mathematical Symbols Used in the Text.
- Includes bibliographical references and indexes.
- Local notes:
- Acquired for the Penn Libraries with assistance from the Lachs-Adler Family Endowed Fund for Collection Development.
Acquired for the Penn Libraries with assistance from the Elizabeth Bowers Peck, 1929 Endowment Book Fund.
- Elizabeth Bowers Peck, 1929 Endowment Book Fund.
Lachs-Adler Family Endowed Fund for Collection Development.
- 0691042896 (acid-free paper)
9780691042893 (acid-free paper)
- Web link:
- Publisher description
The Elizabeth Bowers Peck, 1929 Endowment Book Fund Home Page
The Lachs-Adler Family Endowed Fund for Collection Development Home Page