On the Linear Prediction of Multivariate $(2, p)$-Bounded Processes

Abstract

We develop the linear least squares prediction theory for some classes of nonstationary processes having a Fourier spectral representation. We study time domain as well as spectral domain properties for these processes, such as a Wold decomposition and a decomposition for matrix bimeasures. We also obtain an autoregressive representation for the optimum predictor.