A direct representation for the maximum likelihood estimator of a Gaussian moving average process

It has been known for several years that the maTin-mm likelihood estimator of the parameters of a discrete Gaussian moving average process is efficient and asymptotically normally distributed. A procedure is described in this paper which gives an expression for the maximum likelihood estimator of each parameter as a linear combination of a suitable large set of sample serial correlations. An illustration of this procedure is given.