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• catalog abstract "Some of the key mathematical results are stated without proof in order to make the underlying theory accessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and nonstationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introductions are also given to cointegration and to nonlinear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.".
• catalog contributor b12641596.
• catalog contributor b12641597.
• catalog created "c2002.".
• catalog date "2002".
• catalog date "c2002.".
• catalog dateCopyrighted "c2002.".
• catalog description "Includes bibliographical references (p. [423]-428) and index.".
• catalog description "Introduction -- Stationary Processes -- ARMA Models -- Spectral Analysis -- Modelling and Forecasting with ARMA Processes -- Nonstationary and Seasonal Time Series Models -- Multivariate Time Series -- State-Space Models -- Forecasting Techniques -- Further Topics -- Appendix A: Random Variables and Probability Distributions -- Appendix B: Statistical Complements -- Appendix C: Mean Square Convergence -- Appendix D: An ITSM Tutorial -- References -- Index.".
• catalog description "Some of the key mathematical results are stated without proof in order to make the underlying theory accessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and nonstationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introductions are also given to cointegration and to nonlinear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.".
• catalog description "System requirements for accompanying CD-ROM: IBM PC or equivalent with Windows 95, NT 4.0 or later versions, and 5 MB of hard disk space.".
• catalog extent "xiv, 434 p. :".
• catalog identifier "0387953515 (alk. paper)".
• catalog isPartOf "Springer texts in statistics".
• catalog issued "2002".
• catalog issued "c2002.".
• catalog language "eng".
• catalog publisher "New York : Springer,".
• catalog requires "System requirements for accompanying CD-ROM: IBM PC or equivalent with Windows 95, NT 4.0 or later versions, and 5 MB of hard disk space.".
• catalog subject "519.5/5 21".
• catalog subject "Econometrics.".
• catalog subject "Economics Statistics.".
• catalog subject "Mathematical statistics.".
• catalog subject "QA280 .B757 2002".
• catalog subject "Statistics.".
• catalog subject "Time-series analysis.".
• catalog tableOfContents "Introduction -- Stationary Processes -- ARMA Models -- Spectral Analysis -- Modelling and Forecasting with ARMA Processes -- Nonstationary and Seasonal Time Series Models -- Multivariate Time Series -- State-Space Models -- Forecasting Techniques -- Further Topics -- Appendix A: Random Variables and Probability Distributions -- Appendix B: Statistical Complements -- Appendix C: Mean Square Convergence -- Appendix D: An ITSM Tutorial -- References -- Index.".
• catalog title "Introduction to time series and forecasting / Peter J. Brockwell, Richard A. Davis.".
• catalog type "CD-ROMs. local".
• catalog type "text".