Time Series Analysis - Info and Reading Options
By James D. Hamilton
"Time Series Analysis" was published by Princeton University Press in 1994 - Princeton, NJ, USA, it has 799 pages and the language of the book is English.
“Time Series Analysis” Metadata:
- Title: Time Series Analysis
- Author: James D. Hamilton
- Language: English
- Number of Pages: 799
- Publisher: Princeton University Press
- Publish Date: 1994
- Publish Location: Princeton, NJ, USA
- Dewey Decimal Classification: 519.5/5
- Library of Congress Classification: QA280 .H264 1994
“Time Series Analysis” Subjects and Themes:
- Subjects: Time-series analysis - Statistical analysis - Qa280 .h264 1994 - Qa 280 - 519.5/5
Edition Specifications:
- Format: Hardcover
- Pagination: xiv, 799 p. :
Edition Identifiers:
- Google Books ID: B8_1UBmqVUoC
- The Open Library ID: OL1397451M - OL3906201W
- Online Computer Library Center (OCLC) ID: 28257560
- Library of Congress Control Number (LCCN): 93004958
- ISBN-13: 9780691042893
- ISBN-10: 0691042896
- All ISBNs: 0691042896 - 9780691042893
AI-generated Review of “Time Series Analysis”:
"Time Series Analysis" Table Of Contents:
- 1- Difference equations --
- 2- Lag operators --
- 3- Stationary ARMA processes --
- 4- Forecasting --
- 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 sonstationary time series --
- 16- Processes with deterministic time trends --
- 17- Univariate processes with unit roots --
- 18- Unit roots in multivariate time series --
- 19- Cointegration --
- 20- Full-information maximum likelihood analysis of cointegrated systems --
- 21- Time series models of heteroskedasticity --
- 22- Modeling time series with changes in regime.
"Time Series Analysis" Description:
The Open Library:
The last decade has brought dramatic changes in the way that researchers analyze economic and financial time series. This book synthesizes these recent advances and makes them accessible to first-year graduate students. James Hamilton provides the first adequate text-book treatments of important innovations such as vector autoregressions, generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, he presents basic tools for analyzing dynamic systems (including linear representations, autocovariance generating functions, spectral analysis, and the Kalman filter) in a way that integrates economic theory with the practical difficulties of analyzing and interpreting real-world data. Time Series Analysis fills an important need for a textbook that integrates economic theory, econometrics, and new results. The book is intended to provide students and researchers with a self-contained survey of time series analysis. It starts from first principles and should be readily accessible to any beginning graduate student, while it is also intended to serve as a reference book for researchers. source: https://press.princeton.edu/titles/5386.html
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