A fast estimation method for ARMA processes

被引：3
|
作者：
Sabiti, JK
机构：
[1] Institut de Statistique, Université Libre de Bruxelles, Campus Plaine, 1050 Brussels
来源：
AUTOMATICA | 1996年 / 32卷 / 02期
关键词：
fast algorithm; parameter estimation; least-squares approximations; nonlinear filtering; strong consistency; asymptotic normality;
D O I：
10.1016/0005-1098(96)85553-1
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An improvement of a batch algorithm for parameter estimation of an ARMA process is presented. A fast and iterative algorithm is presented, and provides estimates with the same asymptotic distribution as the maximum likelihood estimates. This algorithm is a modified version of the method suggested by Mayne and Firoozan [(1982). Linear identification of ARMA processes. Automatica, 18, 461-466] and requires one less regression than the previous method, if only one pass is executed.
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页码：235 / 239
页数：5
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