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Introduction to Time Series and Forecasting (Second Edition)

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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. Statisticians and students will learn the latest methods in time series and forecasting, along with modern computational models and algorithms.

Author(s): Peter J. Brockwell, Richard A. Davis,
Edition: 2nd
Year: 2002

Language: English
Pages: 456

Preface......Page 7
Contents......Page 9
1 Introduction......Page 15
2 Stationary Processes......Page 59
3 ARMA Models......Page 97
4 Spectral Analysis......Page 125
5 Modeling and Forecastingwith ARMA Processes......Page 151
6 Nonstationary and SeasonalTime Series Models......Page 193
7 Multivariate Time Series......Page 237
8 State-Space Models......Page 273
9 Forecasting Techniques......Page 331
10Further Topics......Page 345
A Random Variables andProbability Distributions......Page 383
B Statistical Complements......Page 397
C Mean Square Convergence......Page 407
D An ITSM Tutorial......Page 409
References......Page 437
Index......Page 443
ALSO AVAILABLE FROM SPRINGER!......Page 449