Ridge estimation of transfer function weights
作者:
Per-Olov Edlund,
期刊:
Communications in Statistics - Simulation and Computation
(Taylor Available online 1990)
卷期:
Volume 19,
issue 2
页码: 451-468
ISSN:0361-0918
年代: 1990
DOI:10.1080/03610919008812867
出版商: Marcel Dekker, Inc.
关键词: ridge regression;equity estimator;transfer function models;identification procedure;Monte Carlo
数据来源: Taylor
摘要:
In this paper ridge estimators are used to obtain preliminary estimates of the impulse response weights in the Box-Jenkins transfer function model. Five ridge estimators and the Equity estimator are evaluated in a Monte Carlo study covering 5000 different transfer function models. The results show that although the differences between the estimators in most cases are rather small, the Dempster et al estimatorRIDGMand the estimator by Lawless and Wang are best in terms of low average and median squared deviations from the true coefficient vector. Thekvalues by these estimators are most closely correlated with the optimalk(computed from known true values) and also give the highest frequency of lowest squared error and lowest frequency of highest squared error among the investigated estimators.
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