Premium
Automatic Local Smoothing for Spectral Density Estimation
Author(s) -
Fan Jianqing,
Kreutzberger Eva
Publication year - 1998
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/1467-9469.00109
Subject(s) - mathematics , estimator , periodogram , smoothing , bandwidth (computing) , density estimation , spectral density , mathematical optimization , spectral density estimation , algorithm , statistics , mathematical analysis , computer science , fourier transform , computer network
This article uses local polynomial techniques to fit Whittle's likelihood for spectral density estimation. Asymptotic sampling properties of the proposed estimators are derived, and adaptation of the proposed estimator to the boundary effect is demonstrated. We show that the Whittle likelihood‐based estimator has advantages over the least‐squares based log‐periodogram. The bandwidth for the Whittle likelihood‐based method is chosen by a simple adjustment of a bandwidth selector proposed in Fan & Gijbels (1995). The effectiveness of the proposed procedure is demonstrated by a few simulated and real numerical examples. Our simulation results support the asymptotic theory that the likelihood based spectral density and log‐spectral density estimators are the most appealing among their peers