RSS:回归平方和
在学术研究特别是物理学等科学领域中,“回归平方和”(Regression Sum of Squares)是一个常用的统计概念。为了方便书写和表达,通常将其缩写为RSS。该术语用于衡量回归模型中自变量对因变量的解释程度,是分析数据拟合效果的重要指标之一。
Regression Sum of Squares具体释义
Regression Sum of Squares的英文发音
例句
- This paper presents some properties of the SWEEP operator in the scope of least square regression subject to linear constraints and matrix of sum of squares and cross product ( SS & CP ) in singular ill conditions.
- 描述在线性约束条件下,且平方和与交叉乘积矩阵在奇异病态情况下,最小二乘回归扫描算子的一些特性。
- So we use the resampling methods to improve the traditional linear regression equation, and find that it has much more small the residual sum of squares than the usual method by experimental data in the literature with the criterion of the residual sum of squares.
- 为此利用重抽样的方法对传统的线性回归方程进行改进,以预测残差平方和为准则,利用文献中的实验数据进行验证结果是改进的方法比传统的方法的预测残差平方和小。
- The calibration models were established by using single wavelength regression, multiple linear regression, principal component regression, partial least square regression and artificial neural network. The accuracy of the calculated results was estimated with predictive residual error sum of squares ( PRESS ).
- 分别用单波长回归、多元线性回归、主成分回归、偏最小二乘回归和人工神经网络等方法建立校正模型,用预测残差平方和评价计算结果的准确性。
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