Time Series Analysis (Wiley Series in Probability and Statistics)

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9780471361640: Time Series Analysis (Wiley Series in Probability and Statistics)
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"This text demonstrate how to build time series models for univariate and multivariate time series data."(SciTech Book News, Vol. 25, No. 2, June 2001) "...material is thoroughly and carefully presented...a very useful addition to any collection both for learning and reference." (Short Book Reviews, Vol. 21, No. 2, August 2001) "From the preface: 'The book can be used as a principal text or a complementary text for courses in time series.'" (Mathematical Reviews, Issue 2001k) "...an excellent complement...for a first graduate course in time series analysis...a nice addition to anyone's time series library." (Technometrics, Vol. 43, No. 4, November 2001) "...an excellent source of introductory surveys of several timely topics in time series analysis..." (Statistical Papers, July 2002) "...a nice compendium covering a lot of relevant material..." (Statistics & Decisions, Vol.20, No.4, 2002)

From the Publisher:

New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, and signal extraction. They then move on to advanced topics, focusing on heteroscedastic models, nonlinear time series models, Bayesian time series analysis, nonparametric time series analysis, and neural networks. Multivariate time series coverage includes presentations on vector ARMA models, cointegration, and multivariate linear systems. Special features include: * Contributions from eleven of the worlda s leading figures in time series * Shared balance between theory and application * Exercise series sets * Many real data examples * Consistent style and clear, common notation in all contributions *60 helpful graphs and tables Requiring no previous knowledge of the subject, A Course in Time Series Analysis is an important reference and a highly useful resource for researchers and practitioners in statistics, economics, business, engineering, and environmental analysis. An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley editorial department.

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Pena; Tiao; Tsay
Editorial: John Wiley & Sons Limited, New York (2001)
ISBN 10: 047136164X ISBN 13: 9780471361640
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Descripción John Wiley & Sons Limited, New York, 2001. TAPA DURA. Estado de conservación: New. Nº de ref. de la librería 100707874

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Descripción Wiley-Interscience, 2000. Estado de conservación: New. Brand New, Unread Copy in Perfect Condition. A+ Customer Service! Summary: Introduction (D. Pe'a & G. Tiao).BASIC CONCEPTS IN UNIVARIATE TIME SERIES.Univariate Time Series: Autocorrelation, Linear Prediction, Spectrum, State Space Model (G. Wilson).Univariate Autoregressive Moving Average Models (G. Tiao).Model Fitting and Checking, and the Kalman Filter (G. Wilson).Prediction and Model Selection (D. Pe'a).Outliers, Influential Observations and Missing Data (D. Pe'a).Automatic Modeling Methods for Univariate Series (V. Gomez & A. Maravall).Seasonal Adjustment and Signal Extraction in Economic Time Series (V. Gomez & A. Maravall).ADVANCED TOPICS IN UNIVARIATE TIME SERIES.Heteroscedatic Models (R. Tsay).Nonlinear Time Series Models (R. Tsay).Bayesian Time Series Analysis (R. Tsay).Nonparametric Time Series Analysis: Nonparametric Regression, Locally Weighted Regression, Autoregression and Quantile Regression (S. Heiler).Neural Networks (K. Hornik & F. Leisch).MULTIVARIATE TIME SERIES.Vector ARMA Models (G. Tiao).Cointegration in the VAR Model (S. Johansen).Multivariate Linear Systems (M. Deistler).References.Index. Nº de ref. de la librería ABE_book_new_047136164X

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Descripción John Wiley Sons Inc, United States, 2000. Hardback. Estado de conservación: New. New.. 236 x 160 mm. Language: English . Brand New Book. New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, and signal extraction. They then move on to advanced topics, focusing on heteroscedastic models, nonlinear time series models, Bayesian time series analysis, nonparametric time series analysis, and neural networks. Multivariate time series coverage includes presentations on vector ARMA models, cointegration, and multivariate linear systems. Special features include: * Contributions from eleven of the worlda s leading figures in time series * Shared balance between theory and application * Exercise series sets * Many real data examples * Consistent style and clear, common notation in all contributions *60 helpful graphs and tables Requiring no previous knowledge of the subject, A Course in Time Series Analysis is an important reference and a highly useful resource for researchers and practitioners in statistics, economics, business, engineering, and environmental analysis. An Instructor s Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley editorial department. Nº de ref. de la librería AAH9780471361640

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Pena; Tiao; Tsay
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Descripción John Wiley Sons Inc, United States, 2000. Hardback. Estado de conservación: New. New.. 236 x 160 mm. Language: English . Brand New Book. New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, and signal extraction. They then move on to advanced topics, focusing on heteroscedastic models, nonlinear time series models, Bayesian time series analysis, nonparametric time series analysis, and neural networks. Multivariate time series coverage includes presentations on vector ARMA models, cointegration, and multivariate linear systems. Special features include: * Contributions from eleven of the worlda s leading figures in time series * Shared balance between theory and application * Exercise series sets * Many real data examples * Consistent style and clear, common notation in all contributions *60 helpful graphs and tables Requiring no previous knowledge of the subject, A Course in Time Series Analysis is an important reference and a highly useful resource for researchers and practitioners in statistics, economics, business, engineering, and environmental analysis. An Instructor s Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley editorial department. Nº de ref. de la librería AAH9780471361640

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Descripción Wiley-Interscience, 2000. Hardcover. Estado de conservación: New. 1. Nº de ref. de la librería DADAX047136164X

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Descripción Wileyand#8211;Blackwell, 2000. HRD. Estado de conservación: New. New Book.Shipped from US within 10 to 14 business days.THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. de la librería IP-9780471361640

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Descripción 2000. Hardcover. Estado de conservación: New. 1st. 165mm x 30mm x 244mm. Hardcover. New statistical methods and future directions of research in time seriesA Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time s.Shipping may be from multiple locations in the US or from the UK, depending on stock availability. 496 pages. 0.857. Nº de ref. de la librería 9780471361640

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