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John C. Brocklebank - SAS for Forecasting Time Series - 9780471395669 - V9780471395669
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SAS for Forecasting Time Series

€ 136.17
FREE Delivery in Ireland
Description for SAS for Forecasting Time Series Paperback. Written in an easy-to-read style, this comprehensive book shows how the SAS System performs multivariate time series analysis, covering the advanced SAS procedures STATSPACE, ARIMA, and SPECTRA. Num Pages: 424 pages, Illustrations. BIC Classification: PB. Category: (P) Professional & Vocational. Dimension: 280 x 217 x 22. Weight in Grams: 945.
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 ... Read more

Product Details

Format
Paperback
Publication date
2003
Publisher
John Wiley and Sons Ltd United States
Number of pages
424
Condition
New
Number of Pages
424
Place of Publication
New York, United States
ISBN
9780471395669
SKU
V9780471395669
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-50

About John C. Brocklebank
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.

Reviews for SAS for Forecasting Time Series
"The new material and the update of the excellent 1E, now 17 years in the past, certainly make the 2E a necessary purchase for any user of SAS time series modeling methods." Technometrics Vol. 46, No. 1, February 2004

Goodreads reviews for SAS for Forecasting Time Series


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