The Application of the Principle Component Regression(PCR) Model in Increasing Farmers ' Income of Jiangsu Province 基于主成分回归(PCR)模型在江苏省农民增收研究中的应用
Briefly introduces the academic tools of soft measurement based on multivariate statistical project method, such as principle component analysis, principle component regression, partial least squares and neural network. 介绍了基于多元统计投影方法软测量技术的主要数学基础,包括:主元分析、主元回归、偏最小二乘和神经网络,为后续的研究和应用打下理论基础。
Method : The analytic method of principle component regression is applied, and compared with the results of multi stepwise regression. 方法:采用主成分回归(PCR)分析的方法,并与多元逐步回归结果进行比较。
The main theory of MSPC is introduced. It is a technique that making high dimensional space project into low dimensional space. It includes principal component analysis, principle component regression and Partial Least Squares ( PLS ). 重点研究了多变量统计过程控制(MSPC)的主要理论,即把高维空间投影到低维空间的技术,包括主成分分析方法、主成分回归(PCR)和偏最小二乘方法。
Analysis of correlation among physical properties of PU by principle component regression 主成分回归(PCR)法在PU物理性能关系分析中的应用