Optimal window width choice in spectral density estimation - Review and simulation
This paper deals with optimal window width choice in non-parametric lag or spectral window estimation of the spectral density of a stationary zero-mean process. Several approaches are reviewed: cross-validation-based methods as described by Hurvich (1985), Beltrao and Bloomfield (1987) and Hurvich and Beltrao (1990); an iterative procedure developed by Buhlmann (1996); and a bootstrap approach followed by Franke and Hardle (1992). These methods are compared in terms of the mean square error, the mean square percentage error, and a third measure of the distance between the true spectral density and its estimate. The comparison is based on a simulation study, the simulated processes being in the class of ARMA (5,5) processes. On the basis of simulation evidence we suggest to use a slightly modified version of Buhlmann's (1996) iterative method. This paper also makes a minor correction of the bootstrap criterion by Franke and Hardle (1992).
spectral density simulation bandwidth non-parametric estimation