Description: ARMA Model Identification (Springer Series in Statistics)Probability and its Applications Considerable progress has been made in statistical time series analysis. The aim of this book is to present a survey of one of the most active areas in this the identification of autoregressive moving-average models, i.e., determining their orders. Readers are assumed to have already taken one course on time series analysis as might be offered in a graduate course, but otherwise this account is self-contained. The main topics covered Box-Jenkins' method, inverse autocorrelation functions, penalty function identification such as AIC, BIC techniques and Hannan and Quinn's method, instrumental regression, and a range of pattern identification methods. Rather than cover all the methods in detail, the emphasis is on exploring the fundamental ideas underlying them. Extensive references are given to the research literature and as a result, all those engaged in research in this subject will find this an invaluable aid to their work.
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Location: Boston, Massachusetts
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Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 60 Days
Refund will be given as: Money Back
Subject Area: Mathematics
Publication Name: Arma Model Identification
Item Length: 9.5 in
Publisher: Springer
Subject: Probability & Statistics / General, Applied
Publication Year: 1992
Series: Springer Series in Statistics Ser.
Type: Textbook
Format: Hardcover
Language: English
Item Height: .7 in
Author: B. K. Choi
Level: Intermediate, Advanced
Country/Region of Manufacture: United States
Item Width: 6.3 in
Item Weight: 1 lb 5 oz
Number of Pages: Xii, 200 Pages
