拟合方差与回归系数标准偏差存在明显的相关关系。线性模型能解释的方差越大，回归系数标准偏差越小。
It is found that the more the variance explained by the linear model, the smaller the standard deviation of regression coefficient.
以预测集的预测相关系数(r)，预测标准偏差(RMSEP)作为模型评价指标。
The correlation coefficients (r) and root mean square error of prediction (RMSEP) were used as the model evaluation indices.
最终预测结果为两个模型预测值之和， 以模型的预测标准偏差（RMSEP）作为评价指标， 以便考察新方法的有效性。
The final result of the model was the addition of the two model's validation values, and the root mean squared error of prediction (RMSEP) was used to estimate the mixed model.
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