Abstract :
We consider nonparametric estimation of spectral densities of stationary processes,
a fundamental problem in spectral analysis of time series. Under natural and easily
verifiable conditions, we obtain consistency and asymptotic normality of spectral
density estimates. Asymptotic distribution of maximum deviations of the spectral
density estimates is also derived. The latter result sheds new light on the classical
problem of tests of white noises.
