DocumentCode :
1180917
Title :
A note on recursive maximum likelihood for autoregressive modeling
Author :
Vis, Marvin L. ; Scharf, Louis L.
Author_Institution :
Dept. of Electr. & Comput. Eng., Colorado Univ., Boulder, CO, USA
Volume :
42
Issue :
10
fYear :
1994
fDate :
10/1/1994 12:00:00 AM
Firstpage :
2881
Lastpage :
2883
Abstract :
Rederives recursive maximum likelihood (RML) for an autoregressive (AR) time series using the Levinson decomposition. This decomposition produces a recursive update of the likelihood function for the AR parameters in terms of the reflection coefficients, prediction error variances, and forward and backward prediction errors. A fast algorithm for this recursive update is presented and compared with the recursive updates of the Burg (1975) algorithm. The comparison clarifies the connection between Burg´s algorithm and RML
Keywords :
correlation methods; error analysis; estimation theory; filtering and prediction theory; matrix algebra; maximum likelihood estimation; stochastic processes; time series; Burg´s algorithm; Levinson decomposition; autoregressive modeling; backward prediction errors; fast algorithm; forward and backward prediction errors; prediction error variances; recursive maximum likelihood; reflection coefficients; Covariance matrix; Error correction; Filters; Gaussian noise; Maximum likelihood estimation; Parameter estimation; Probability; Random variables; Reflection; Statistics;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/78.324761
Filename :
324761
Link To Document :
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