Robust spectral regression
Let \(y_ t=x'_ t\beta +u_ t\), \(t\in Z^ 1\), where the disturbances \(u_ t\) follow a second-order stationary process with E \(u_ t=0\). The spectral density f(\(\lambda)\) of a process \(u_ t\) is unknown but belongs to a neighborhood of some special spectral density \(f_ 0(\lambda)\). Using methods developed in robust statistics, the problem of the efficiency of linear (in the y's) estimators of \(\beta\) is considered.
scientific article; zbMATH DE number 4050819