The Resource Time series analysis, James D. Hamilton
Time series analysis, James D. Hamilton
Resource Information
The item Time series analysis, James D. Hamilton represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of San Diego Libraries.This item is available to borrow from 1 library branch.
Resource Information
The item Time series analysis, James D. Hamilton represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of San Diego Libraries.
This item is available to borrow from 1 library branch.
- Summary
- "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."--Jacket
- Language
- eng
- Extent
- 1 online resource (xiv, 799 pages)
- Contents
-
- Difference equations
- Lag operators
- Stationary ARMA processes
- Forecasting
- Maximum likelihood estimation
- Spectral analysis
- Asymptotic distribution theory
- Linear regression models
- Linear systems of simultaneous equations
- Covariance-stationary vector processes
- Vector autoregressions
- Bayesian analysis
- The Kalman filter
- Generalized method of moments
- Models of sonstationary time series
- Processes with deterministic time trends
- Univariate processes with unit roots
- Unit roots in multivariate time series
- Cointegration
- Full-information maximum likelihood analysis of cointegrated systems
- Time series models of heteroskedasticity
- Modeling time series with changes in regime
- Isbn
- 9780691218632
- Label
- Time series analysis
- Title
- Time series analysis
- Statement of responsibility
- James D. Hamilton
- Language
- eng
- Summary
- "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."--Jacket
- Cataloging source
- HS0
- http://library.link/vocab/creatorDate
- 1954-
- http://library.link/vocab/creatorName
- Hamilton, James D.
- Illustrations
- illustrations
- Index
- index present
- Literary form
- non fiction
- Nature of contents
-
- dictionaries
- bibliography
- http://library.link/vocab/subjectName
-
- Time-series analysis
- Série chronologique
- BUSINESS & ECONOMICS / Investments & Securities / General
- Méthodes statistiques
- Séries temporelles
- Time-series analysis
- Tijdreeksen
- Séries chronologiques
- Statistique mathématique
- Mathématiques économiques
- Économétrie
- Time-series analysis
- Label
- Time series analysis, James D. Hamilton
- Bibliography note
- Includes bibliographical references and indexes
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- Difference equations -- Lag operators -- Stationary ARMA processes -- Forecasting -- Maximum likelihood estimation -- Spectral analysis -- Asymptotic distribution theory -- Linear regression models -- Linear systems of simultaneous equations -- Covariance-stationary vector processes -- Vector autoregressions -- Bayesian analysis -- The Kalman filter -- Generalized method of moments -- Models of sonstationary time series -- Processes with deterministic time trends -- Univariate processes with unit roots -- Unit roots in multivariate time series -- Cointegration -- Full-information maximum likelihood analysis of cointegrated systems -- Time series models of heteroskedasticity -- Modeling time series with changes in regime
- Control code
- on1108965724
- Extent
- 1 online resource (xiv, 799 pages)
- Form of item
- online
- Isbn
- 9780691218632
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Note
- JSTOR
- Other control number
- 9780691042893
- Other physical details
- illustrations
- http://library.link/vocab/ext/overdrive/overdriveId
- 22573/ctv14jn21q
- Specific material designation
- remote
- System control number
- (OCoLC)1108965724
- Label
- Time series analysis, James D. Hamilton
- Bibliography note
- Includes bibliographical references and indexes
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- Difference equations -- Lag operators -- Stationary ARMA processes -- Forecasting -- Maximum likelihood estimation -- Spectral analysis -- Asymptotic distribution theory -- Linear regression models -- Linear systems of simultaneous equations -- Covariance-stationary vector processes -- Vector autoregressions -- Bayesian analysis -- The Kalman filter -- Generalized method of moments -- Models of sonstationary time series -- Processes with deterministic time trends -- Univariate processes with unit roots -- Unit roots in multivariate time series -- Cointegration -- Full-information maximum likelihood analysis of cointegrated systems -- Time series models of heteroskedasticity -- Modeling time series with changes in regime
- Control code
- on1108965724
- Extent
- 1 online resource (xiv, 799 pages)
- Form of item
- online
- Isbn
- 9780691218632
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Note
- JSTOR
- Other control number
- 9780691042893
- Other physical details
- illustrations
- http://library.link/vocab/ext/overdrive/overdriveId
- 22573/ctv14jn21q
- Specific material designation
- remote
- System control number
- (OCoLC)1108965724
Subject
- Mathématiques économiques
- Méthodes statistiques
- Statistique mathématique
- Série chronologique
- Séries chronologiques
- Séries temporelles
- BUSINESS & ECONOMICS / Investments & Securities / General
- Time-series analysis
- Time-series analysis
- Time-series analysis
- Économétrie
- Tijdreeksen
- Electronic books
Genre
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.sandiego.edu/portal/Time-series-analysis-James-D.-Hamilton/iWEjGA5-6T4/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.sandiego.edu/portal/Time-series-analysis-James-D.-Hamilton/iWEjGA5-6T4/">Time series analysis, James D. Hamilton</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.sandiego.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.sandiego.edu/">University of San Diego Libraries</a></span></span></span></span></div>
