Asymptotically Efficient Nonparametric Estimation of Nonlinear Spectral Functionals

The paper considers a problem of construction of asymptotically efficient estimators for functionals defined on a class of spectral densities. We define the concepts of H ₀- and IK-efficiency of estimators, based on the variants of Hájek–Ibragimov–Khas'minskii convolution theorem and Hájek–Le Cam local asymptotic minimax theorem, respectively. We prove that is a suitable sequence of T ^1/2-consistent estimators of unknown spectral density (), is H ₀- and IK-asymptotically efficient estimator for a nonlinear smooth functional ().