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偏最小二乘建模在R软件中的实现及实证分析
引用本文:齐琛,方秋莲.偏最小二乘建模在R软件中的实现及实证分析[J].数学理论与应用,2013(2):103-111.
作者姓名:齐琛  方秋莲
作者单位:中南大学数学与统计学院,长沙410075
基金项目:湖南省自然科学基金资助项目(编号:12JJ5002)
摘    要:通过介绍偏最小二乘(PLS)的建模和显著性检验原理,解决了小样本多变量且变量间存在多重共线性的回归问题,建立了多变量对多变量的回归模型,并使用R软件(版本为Ri3862.15.1)实现了PLS建模;最后基于葡萄和葡萄酒理化指标数据进行了实证分析.

关 键 词:偏最小二乘  R语言  jackknife方差  显著性检验

Partial Least Squares Modelling with R Software and Empirical Analysis
Qi Chen,Fang Qiulian.Partial Least Squares Modelling with R Software and Empirical Analysis[J].Mathematical Theory and Applications,2013(2):103-111.
Authors:Qi Chen  Fang Qiulian
Institution:(School of Mathematics and Statistics, Central South University, Changsha 410075, China)
Abstract:This paper introduces the Partial Least Squares (PLS) method and its significance test principle for model-ling regression problems in which sample size is small and there is muhicollinearity among observable variables, and furthermore, illustrates how to set up PLS models with the R software. An example to model the relation of the physi-cochemical indexes between gapes and wine is given to demonstrate the modelling process.
Keywords:PLS  R Language  Jackknife Variance  Significance Test
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