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000 camMa
001 2210080896687
003 OCoLC
005 20210225114209
006 m d
007 cr |||||||||||
008 031104t19941994njua ob 001 0 eng d
019 a1195465248a1226712568
020 a0691042896q(acid-free paper)
020 a9780691042893
020 a9780691218632q(electronic bk.)
020 a0691218633q(electronic bk.)
024 a9780691042893
035 a2541224b(NT)
035 a(OCoLC)1108965724z(OCoLC)1195465248z(OCoLC)1226712568
037 a22573/ctv14jn21qbJSTOR
040 aHS0bengcHS0dOCLCOdOCLCFdOCLCQdJSTORdYDXdCUSdUKAHLdNd221008
050 aQA280b.H264 1994
060 aQA 280
072 aBUSx0360002bisacsh
080 a512.8
082 a519.5/5220
084 a31.732bcl
084 a*62M102msc
084 a31.552bcl
084 a62-012msc
084 a62M152msc
084 a62P202msc
084 aPF 352blsrissc
100 aHamilton, James D.q(James Douglas),d1954-eauthor.
245 00 aTime series analysis /cJames D. Hamilton.
260 aPrinceton, N.J. :bPrinceton University Press,c[1994]
300 a1 online resource (xiv, 799 pages) :billustrations
336 atextbtxt2rdacontent
337 acomputerbc2rdamedia
338 aonline resourcebcr2rdacarrier
504 aIncludes bibliographical references and indexes.
505 aDifference 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.
520 a"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.
588 aOnline resource; title from PDF title page (JSTOR, viewed October 22, 2020).
590 aOCLC control number change
650 aTime-series analysis.
650 aSe?rie chronologique.
650 aBUSINESS & ECONOMICS / Investments & Securities / General2bisacsh
650 aMe?thodes statistiques.2eclas
650 aSe?ries temporelles.2eclas
650 aTime-series analysis.2fast0(OCoLC)fst01151190
650 aTijdreeksen.2gtt
650 aSe?ries chronologiques.2ram
650 aStatistique mathe?matique.2ram
650 aMathe?matiques e?conomiques.2ram
650 aE?conome?trie.2ram
650 aTime-series analysis.2nli
655 aElectronic books.
776 cOriginalz0691042896z9780691042893w(DLC) 93004958w(OCoLC)28257560
776 iPrint version:aHamilton, James D. (James Douglas), 1954-tTime series analysis.dPrinceton, N.J. : Princeton University Press, 짤1994z0691042896w(DLC) 93004958w(OCoLC)28257560
856 3EBSCOhostuhttp://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=2541224
938 aAskews and Holts Library ServicesbASKHnAH37760676
938 aYBP Library ServicesbYANKn16872997
938 aEBSCOhostbEBSCn2541224
994 a92bN
Time series analysis /James D. Hamilton
종류
전자책
서명
Time series analysis /James D. Hamilton
저자명
발행사항
Princeton, N.J. : Princeton University Press [1994]
형태사항
1 online resource (xiv, 799 pages) : illustrations
주기사항
Includes bibliographical references and indexes. / "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.
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