ESTIMATING WEAK ARMA REPRESENTATIONS UNDE R MIXING CONDITIONS

A large class of nonlinear processes admit weak ARMA representations. We propose an estimation procedure based on the minimization of a sum of squared deviations about linear conditional expectations. Strong co nsistency and asymptotic normality are shown to hold for the estimator under ergodic and mixing assumptions.