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008			100301s2002 xxu| s |||| 0|eng d
020			_a9780387216577 _9978-0-387-21657-7
082			_a510.285 _223
100			_aBrockwell, Peter J. _919582
245			_aIntroduction to Time Series and Forecasting _h[electronic resource] / _cby Peter J. Brockwell, Richard A. Davis.
250			_a2nd ed. 2002.
260			_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2002.
300			_aXIV, 437 p. _bonline resource.
505			_aStationary 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.
520			_aSome 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.
650			_aComputer software. _919583
650			_aProbabilities. _919584
650			_aStatistics . _919585
650			_aEconometrics. _919586
650			_aMathematical Software. _919587
650			_aProbability Theory. _919588
650			_aStatistical Theory and Methods. _919589
650			_aStatistics in Business, Management, Economics, Finance, Insurance. _919590
650			_aEconometrics. _919586
650			_aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences. _919591
700			_aDavis, Richard A. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _919592
856			_uhttps://doi.org/10.1007/b97391
942			_cEBK
999			_c13540 _d13540