Prediction error identification methods for stationary stochastic processes

The strong consistency of a general class of prediction error identification methods for stationary stochastic processes is demonstrated. In particular, the strong consistency of the maximum likelihood method for stationary Gaussian processes [4], [5] and of the quadratic loss prediction error method for stationary stochastic processes [1]-[3] follow as special cases of the general result.