Multiblock latent root regression. Application to epidemiological data

被引:5
作者
Bougeard, Stephanie
Hanafi, Mohamed
Qannari, El Mostafa
机构
[1] AFSSA, Dept Epidemiol Anim, F-22440 Ploufragan, France
[2] INRA, ENITIAA, Unite Sensometrie & Chimiometrie, F-44322 Nantes, France
关键词
latent root regression; multiblock analysis; latent variables; partial least square regression;
D O I
10.1007/s00180-007-0036-1
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Several papers have already stressed the interest of latent root regression and its similarities to partial least squares regression. A new formulation of this method which makes it even simpler than the original method to set up a prediction model is discussed. Furthermore, it is shown how this method can be extended not only to the case where it is desired to predict several response variables from a set of predictors but also to the multiblock setting where the aim is to predict one or several data sets from several other data sets. The interest of the method is illustrated on the basis of a data set pertaining to epidemiology.
引用
收藏
页码:209 / 222
页数:14
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