由历史数据推测未来趋势的众多方法中较突出的有：时间序列法、最小平方法、指数平滑法、回归分析和相关分析。
Prominent among the various techniques that can help to extrapolate past date into future trends are the following:time series, least squares method, exponential smoothing, regression and correlation.
本文由试验得到的体温数据，分别用假设检验和时间序列分析方法，找到辨别寒热性的数学依据。
In this paper, the data of body temperature from experiment is studied by using the methods of hypothesis test and time series analysis, then the mathematical basis of identifying the nature is found.
采用线性插值及双线性插值得到预测点位置上的本征模态值。 结构由原风压场协方差分析得到的主坐标和上述新本征模态值获得未布置测压点位置的风压时间序列。
The linear interpolation and bilinear interpolation were employed to obtain the values of the proper modes on locations where the wind pressure time series are to be predicted.
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