主元回归和部分最小二乘方法能克服批次内不同阶段的控制量存在的相关关系从而得到更准确的模型。

The regression analyses to correlate the control actions with the results for various stages of a batch to obtain more accurate models.

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介绍了多变量统计投影方法的主要理论基础，包括：主元分析(PCA)、主元回归(PCR)、偏最小二乘(PLS)。

The paper briefly introduced the theoretical foundation of MSP method, which include Principle Component Analysis (PCA), Principle Component Regression (PCR), and Partial Least Squares (PLS).

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介绍了多变量统计投影方法的主要理论基础，包括：主元分析(PCA)、主元回归(PCR)、偏最小二乘(PLS)。

The paper briefly introduced the theoretical foundation of MSP method, which include Principle Component Analysis (PCA), Principle Component Regression (PCR), and Partial Least Squares (PLS).

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