Introduction to Time Series and Forecasting by Peter J. Brockwell (English) Pape

Description: Introduction to Time Series and Forecasting by Peter J. Brockwell, Richard A. Davis This is an introduction to time series that emphasizes methods and analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher 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. Table of Contents Stationary Processes.- ARMA Models.- Spectral Analysis.- Modeling and Forecasting with ARMA Processes.- Nonstationary and Seasonal Time Series Models.- Multivariate Time Series.- State-Space Models.- Forecasting Techniques.- Further Topics.- Erratum. Review From the reviews:"The emphasis is on hands-on experience and the friendly software that accompanies the book serves the purpose admirably. ...The authors should be congratulated for making the subject accessible and fun to learn. The book is a pleasure to read and highly recommended. I regard it as the best introductory text in town." ISI Short Book Reviews Promotional Springer Book Archives Long Description This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied in economics, engineering, and the natural and social sciences. The book assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This second edition contains detailed instructions on the use of the new totally windows-based computer package ITSM2000. Expanded treatments are also given of several topics treated only briefly in the first edition. These include regression with time series errors, which plays an important role in forecasting and inference, and ARCH and GARCH models, which are widely used for the modeling of financial time series. These models can be fitted using the new version of ITSM. 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 the Burg and Hannan-Rissanen algorithms, unit roots, the EM algorithm, structural models, 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 non-linear, continuous-time and long-memory models. Review Quote From the reviews: "The emphasis is on hands-on experience and the friendly software that accompanies the book serves the purpose admirably. ... The authors should be congratulated for making the subject accessible and fun to learn. The book is a pleasure to read and highly recommended. I regard it as the best introductory text in town." ISI Short Book Reviews Feature Includes supplementary material: sn.pub/extras Request lecturer material: sn.pub/lecturer-material Description for Sales People This book is aimed at the reader who wishes to gain a working knowldege of time series and forecasting methods as applied in economics, engineering, and the natural and social sciences. Details ISBN1475777507 Author Richard A. Davis Language English ISBN-10 0387953515 Short Title INTRO TO TIME SERIES & FORECAS Series Springer Texts in Statistics Media Book Year 2013 Publication Date 2013-04-23 Imprint Springer-Verlag New York Inc. Place of Publication New York, NY Country of Publication United States Birth 1925 Illustrations XIV, 437 p. AU Release Date 2013-04-23 NZ Release Date 2013-04-23 US Release Date 2013-04-23 UK Release Date 2013-04-23 Pages 437 Publisher Springer-Verlag New York Inc. Edition Description 2nd ed. 2002. Softcover reprint of the original 2nd ed. 2002 Edition 2nd ISBN-13 9781475777505 Format Paperback Alternative 9780387953519 DEWEY 519.55 Audience Professional & Vocational Replaces 9780387947198 Replaced by 9783319298528 We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:96346401;

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