Maximum entropy spectral analysis and ARMA processes (Corresp.)

The maximum entropy spectral analysis for discrete-time stationary processes was first proposed by J. P. Burg. He showed that if a finite number of covariance lag values of a stationary process are known, then an autoregressive (AR) process with the given autocorrelation values best fits the given constraints in the sense of maximizing thc differential entropy rate of the model. A more general type of prior knowledge of the process is considered, and it is shown that the maximum entropy method, subject to our constraints, is equivalent to fitting a mixed autoregressive moving average (ARMA) model.