×


 x 

Shopping cart
Ladiray, Dominique; Quenneville, Benoit - Seasonal Adjustment with the X-11 Method - 9780387951713 - V9780387951713
Stock image for illustration purposes only - book cover, edition or condition may vary.

Seasonal Adjustment with the X-11 Method

€ 146.33
FREE Delivery in Ireland
Description for Seasonal Adjustment with the X-11 Method Paperback. Documents the seasonal adjustment method implemented in the X-11 based software. This work outlines the X-11 methodology, devoting a chapter to the study of moving averages with an emphasis on those used by X-11. It serves as an important reference for government agencies, macroeconomists, and other users of economic data. Series: Lecture Notes in Statistics. Num Pages: 278 pages, biography. BIC Classification: KCHS; PBT; UFM. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 13. Weight in Grams: 364.
The authors, Dominique Ladiray and Benoit Quenneville, provide a unique and comprehensive r~view of the X-11 Method of seasonal adjustment. They review the original X-11 Method developed at the US Bureau of the Census in the mid-1960's, the X-ll core of the X-ll-ARTMA Method developed at Statistics Canada in the 1970's, and the X-11 module in the X- 12-ARTMA Method developed more recently at the Bureau of the Census. The review will prove extremely useful to anyone working in the field of seasonal adjustment who wants to understand the X-11 Method and how it fits into the broader picture of ... Read more

Product Details

Format
Paperback
Publication date
2001
Publisher
Springer-Verlag New York Inc. United States
Number of pages
278
Condition
New
Series
Lecture Notes in Statistics
Number of Pages
256
Place of Publication
New York, NY, United States
ISBN
9780387951713
SKU
V9780387951713
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

Reviews for Seasonal Adjustment with the X-11 Method

Goodreads reviews for Seasonal Adjustment with the X-11 Method


Subscribe to our newsletter

News on special offers, signed editions & more!