Automatic Frequency Domain Inference on Semiparametric and Nonparametric Models
研究频域时间序列分析中基于数据的平滑方法，证明谱估计的一致收敛性，并将其应用于半参数模型，通过交叉验证实现自动平滑，得到可行的最优参数估计。
The author considers frequency domain time series analysis, where smoothing in nonparametric spectrum estimation is data-dependent. Uniform convergence of spectrum estimates is established and applied to a semiparametric model, parameterized over possibly only a subset of the frequencies, in which disturbances have nonparametric autocorrelation. Optimal instruments depend on the disturbance spectrum and frequency response function, which is nonparametric in incomplete systems. The author justifies feasible, optimal parameter estimates. The degree of smoothing is allowed to depend on the data in a general way. The author proves consistency of a cross-validation method of automatic smoothing and applies it to a semiparametric model. Copyright 1991 by The Econometric Society.