The current study established ARIMA(2,2,0) model, one-parameter double exponential smoothing model, Holt-Winters two-parameter double exponential smoothing model, ) infectious disease model-based autoregression model, principal component regression model with time factor AR(2)-EGARCH(0,2) model.
建立了ARIMA(2,2,0)模型、单参数双重指数平滑模型、Holt-Winters两参数双重指数平滑模型、基于传染病模型的自回归模型、带有时间因素的主成分回归模型和AR(2)-EGARCH(0,2)模型。
参考来源 - 时间序列分析在短周期高发病率事件预测中的应用研究·2,447,543篇论文数据，部分数据来源于NoteExpress
This paper considers the classification compression principal component estimate of regression coefficient in growth curve model and proves that it is superior to least squares estimate.
研究岭型主成分估计在降维估计类中的方差最优性，证明了它的方差阵在降维估计类中最小，方差阵的特征值最小，方差和及方差积最小。
A predicated model of the subjective thermal feeling with physiological indices is built up by principal component regression analysis. Therefore, a quantitative method to …
通过主成分回归建立了用生理指标预测主观热感觉的模型，从而得出一种定量地评价服装属性的方法。
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