SAS for Forecasting Time Series

2. Auflage 2003
ISBN: 978-0-471-39566-9
Verlag: Wiley

Buch, Englisch, 424 Seiten, Format (B × H): 210 mm x 280 mm, Gewicht: 1031 g

Easy-to-read and comprehensive, this book shows how the SAS System performs multivariate time series analysis and features the advanced SAS procedures STATSPACE, ARIMA, and SPECTRA. The interrelationship of SAS/ETS procedures is demonstrated with an accompanying discussion of how the choice of a procedure depends on the data to be analysed and the reults desired. Other topics covered include detecting sinusoidal components in time series models and performing bivariate corr-spectral analysis and comparing the results with the standard transfer function methodology. The authors? unique approach to integrating students in a variety of disciplines and industries. Emphasis is on correct interpretation of output to draw meaningful conclusions. The volume, co-pubished by SAS and JWS, features both theory and practicality, and accompanies a soon-to-be extensive library of SAS hands-on manuals in a multitude of statistical areas. The book can be used with a number of hardware-specific computing machines including CMS, Mac, MVS, Opem VMS Alpha, Opmen VMS VAX, OS/390, OS/2, UNIX, and Windows.

Autoren/Hrsg.

Brocklebank, John C

Dickey, David A

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Computeranwendungen in der Mathematik

Inhaltsverzeichnis

Chapter 1- Overview of Time Series.

Chapter 2- Simple Models: Autoregression.

Chapter 3- The General ARIMA Model.

Chapter 4- The ARIMA Model: Introductory Applications.

Chapter 5- The ARIMA Model: Special Applications.

Chapter 6- State Space Modeling.

Chapter 7- Spectral Analysis.

Über Autor(innen)

John C. Brocklebank is Mgr. of Stats. Training at the SAS Institute. David A. Dickey is Associate Professor of Statistics at North Carolina State University.