A class of spectral density estimators

A class of spectral windows depending on one parameter is presented and shown to include many of the common windows. The mean square rate of convergence of the associated spectral density estimators are calculated in terms of this parameter for spectral densities which are locally Lipschitz continuous The class is shown to include certain data tapers and data windows corresponding to missing observations. This is true also for the kernels of (C−α) summability which provide means for estimating the spectral density when the covariance function is periodic.