DocumentCode :
834525
Title :
An adaptive d-step ahead predictor based on least squares
Author :
Sin, Kwai Sang ; Goodwin, Graham C. ; Bitmead, Robert R.
Author_Institution :
University of Newcastle, Newcastle, N.S.W., Australia
Volume :
25
Issue :
6
fYear :
1980
fDate :
12/1/1980 12:00:00 AM
Firstpage :
1161
Lastpage :
1165
Abstract :
This paper examines the asymptotic properties of a least squares algorithm for adaptively calculating a 
-step ahead prediction of a time series. It is shown that, with probability one, the sample mean-square difference between time recursive prediction and the optimal linear prediction converges to zero. Relatively weak assumptions are required regarding the underlying model of the time series.
-step ahead prediction of a time series. It is shown that, with probability one, the sample mean-square difference between time recursive prediction and the optimal linear prediction converges to zero. Relatively weak assumptions are required regarding the underlying model of the time series.Keywords :
Adaptive estimation; Autoregressive moving-average processes; Least-squares estimation; Parameter estimation; Prediction methods; Control systems; Decision theory; Distributed control; Dynamic programming; Integral equations; Least squares methods; Optimal control; Parameter estimation; Stochastic processes; Stochastic systems;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/TAC.1980.1102539
Filename :
1102539
Link To Document :
