A note on recursive maximum likelihood for autoregressive modeling
Date
1994
Authors
Vis, Marvin L., author
Scharf, Louis L., author
IEEE, publisher
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Abstract
In this paper, we rederive 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 algorithm. The comparison clarifies the connection between Burg's algorithm and RML.
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Rights Access
Subject
matrix algebra
maximum likelihood estimation
time series
correlation methods
error analysis
estimation theory
stochastic processes
filtering and prediction theory