Introduction to time series and forecasting

Peter J. Brockwell, Richard A. Davis - Collection Springer texts in statistics

440 pages, parution le 20/04/2004 (2^eme édition)

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Résumé

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.

Sommaire

Stationary processes
Arma models
Spectral analysis
Modelling and prediction with arma processes
State-space models
Forecasting techniques

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Peter J. Brockwell, Richard A. Davis
Collection	Springer texts in statistics
Parution	20/04/2004
Édition	2^eme édition
Nb. de pages	440
Format	21 x 24
Couverture	Relié
Poids	1054g
Intérieur	Noir et Blanc
EAN13	9780387953519
ISBN13	978-0-387-95351-9