Optimal linear time-invariant (LTI) approximation of discrete-time nonlinear systems is studied using a quasi-stationary signal description. The optimality of the LTI approximation is quantified as a least average squared error condition, reminescent of recent studies on the performance of least squares type identification methods for LTI models of nonlinear systems.