Generalized Schur parametrization and orthogonal modeling algorithms for second-order time-series

We present algorithms for orthogonal Schur parametrization, innovations transformation and stochastic modeling of second-order non-stationary time-series, showing statistical equivalence (in a weak second-order sense) of the parametrized and modeled time-series.