The aim of this paper is to give a systematic account of asymptotic properties of the sample autocovariance, autocorrelation and partial autocorrelation functions of linear stationary time series.
本文的目的在于，对于线性平稳时间序列的样本、自协方差、自相关和偏相关函数的渐近性质，给出一个比较系统的描述。
Most of the popular clustering methods are designed for the linear time series, assuming that the stationary time series can be fitted by linear model. In fact, the true word is nonlinear.
由于现实世界中时间序列多数是非线性的，而现有的时间序列聚类问题大多是基于线性时间序列模型进行聚类的，提出了可以用于非线性时间序列的聚类方法。
Most of the popular clustering methods are designed for the linear time series, assuming that the stationary time series can be fitted by linear model. In fact, the true word is nonlinear.
由于现实世界中时间序列多数是非线性的，而现有的时间序列聚类问题大多是基于线性时间序列模型进行聚类的，提出了可以用于非线性时间序列的聚类方法。
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