Introduction to Time Series and Forecasting | 
 enlarge | Authors: Peter J. Brockwell, Richard A. Davis
Publisher: Springer
Category: Book
List Price: $109.00
Buy New: $70.85
You Save: $38.15 (35%)
New (32) Used (16) from $55.95
Rating:  10 reviews
Sales Rank: 120180
Media: Hardcover
Edition: 2nd
Pages: 456
Number Of Items: 1
Shipping Weight (lbs): 2.3
Dimensions (in): 9 x 8.1 x 1.4
ISBN: 0387953515
Dewey Decimal Number: 519.55
EAN: 9780387953519
Publication Date: March 12, 2003
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Condition: New Book. International Shipping Available
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Product 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, the student version of which is included with the text. 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.
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| Customer Reviews: Read 5 more reviews...
 Excellent introduction on time series analysis January 31, 2001
Steve Uhlig (Delft, The Netherlands)
36 out of 37 found this review helpful
Very good introductory book to ARMA models. Full of real-life examples that provide some intuitive insight about the issues that may arise when modelling time series and forecasting. Requires some initial knowledge in statistics and algebra but if you're involved in time series modelling, it should be your first book.
excellent introduction for students and practitioners July 8, 2002
Michael R. Chernick (Malvern, PA)
45 out of 48 found this review helpful
In contrast to their graduate text "Time Series: Theory and Methods" this book is more elementary and introductory and is pitched at the advanced undergraduate level requiring only calculus, elementary statistics and matrix algebra. It gives very good coverage to a wide variety of time series models and includes some nonstationary models. In this second edition the chapter on nonstationary models includes the latest coverage of ARCH and GARCH models presented in a way that I found very accessible.Computations are done with ITSM and in this edition the ITSM 2000 version 7.0 edition is included on a CD so that students can reproduce the authors' calculations and run analyses of their own. Another nice feature of the text that distinguishes it from other texts at this level is the introduction of multivariate time series, coverage of state space models, chaos and cointegration. Ideas are illustrated with examples. Important theory is discussed but is kept brief and theorems and proofs are not given to the extent of their other more theoretical text.
good modern cover of both time and frequency domains January 23, 2008
Michael R. Chernick (Holland PA)
25 out of 25 found this review helpful
In contrast to their graduate text "Time Series: Theory and Methods" this book is more elementary and introductory and is pitched at the advanced undergraduate level requiring only calculus, elementary statistics and matrix algebra. It gives very good coverage to a wide variety of time series models and includes some nonstationary models. In this second edition the chapter on nonstationary models includes the latest coverage of ARCH and GARCH models presented in a way that I found very accessible.
Computations are done with ITSM and in this edition the ITSM 2000 version 7.0 edition is included on a CD so that students can reproduce the authors' calculations and run analyses of their own.
Another nice feature of the text that distinguishes it from other texts at this level is the introduction of multivariate time series, coverage of state space models, chaos and cointegration. Ideas are illustrated with examples. Important theory is discussed but is kept brief and theorems and proofs are not given to the extent of their other more theoretical text.
Best introduction to time series analysis August 14, 2000
Steve Uhlig (Namur, Belgium)
15 out of 19 found this review helpful
Very good introductory book to ARMA models. Full of real-life examples that provide some intuitive insight about the issues that may arise when modelling time series and forecasting. Requires some initial knowledge in statistics and algebra but if you're involved in time series modelling, it should be your first book.
Great book for a great price February 12, 2004
5 out of 6 found this review helpful
This is one of those books that you can't find much cons to it. The book is inexpensive, and it's unbelievably lightweight. The material is rich, and yet easy to understand. The author actually brings you step by step from elementary to theorectical proofs.
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