Principal component analysis (PCA) and partial least squares (PLS) are the conventional techniques of multivariate statistical process control but exist some defects.
在多变量统计过程控制中，传统的方法主要包括主元分析和偏最小二乘，这些方法存在着诸多缺陷。
This paper use partial least squares regression analysis and quarter of the model to identify the key factors affecting customer satisfaction.
本文利用偏最小二乘回归分析方法和四分模型找出影响顾客满意度的关键因素。
In this paper the factor analysis method is presented to transform orthogonally the optimal subspace, which is obtained from partial least squares regression.
本文提出采用因素分析方法，对偏最小二乘回归的最优子空间进行正交变换。
The NIR quantitative analysis models of 5 detection indexes in validation set was established using partial least squares(PLS) method.
采用偏最小二乘法分别建立校正集样本中5个检测指标的NIR定量分析模型，并对验证集样本进行预测。
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).
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)。
Obtained: Partial Least Squares iterative algorithm to handle data sheet leaflet extraction equivalence with Principal Component Analysis.
证明出，偏最小二乘迭代算法在处理单张数据表成分提取时与主成分分析相同。
About multivariate statistical process, three methods are introduced: Principal Component Analysis, Partial Least Squares, Kernel Density Estimation.
多元统计过程介绍了三种主要的方法：主元分析法、偏最小二乘法和核函数概率密度估计法。
About multivariate statistical process, three methods are introduced: Principal Component Analysis, Partial Least Squares, Kernel Density Estimation.
多元统计过程介绍了三种主要的方法：主元分析法、偏最小二乘法和核函数概率密度估计法。
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