首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Multiblock latent root regression. Application to epidemiological data
Authors:Stéphanie Bougeard  Mohamed Hanafi  El Mostafa Qannari
Institution:(1) Département d’épidémiologie animale, Les Croix, AFSSA, BP53, 22440 Ploufragan, France;(2) ENITIAA-INRA, Unité de Sensométrie et Chimiométrie, Rue de la Géraudière, BP 82225, 44322 Nantes Cedex, France
Abstract: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.
Keywords:Latent root regression  Multiblock analysis  Latent variables  Partial least square regression
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号