Signal Extraction for Finite Nonstationary Time Series
针对信号和噪声均为非平稳ARIMA模型的情况，利用Ansley和Kohn的变换方法，基于有限观测数据构建信号估计并计算其均方误差，同时给出高效算法。
For a signal plus noise model, where both signal and noise are generated by nonstation ary ARIMA, autoregressive integrated moving average, models, we use the transformation approach of Ansley & Kohn (1985) to construct an estimate of the signal and obtain its mean squared error given a finite number of observations. A method for efficient computation of the signal estimate and its mean squared error is also presented.