ASYMPTOTICS OF SPECTRAL DENSITY ESTIMATES
研究了平稳过程谱密度的非参数估计，在自然可验证条件下证明了估计量的相合性和渐近正态性，并推导了最大偏差的渐近分布，为白噪声检验提供了新视角。
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.