  Improved performance in higher-order spectral density estimation is achieved
using a general class of infinite-order kernels. These estimates are
asymptotically less biased but with the same order of variance as compared to
the classical estimators with second-order kernels. A simple, data-dependent
algorithm for selecting bandwidth is introduced and is shown to be consistent
with estimating the optimal bandwidth. Bispectral simulations with several
standard models are used to demonstrate the performance of the proposed
methodology.
