首页 | 本学科首页   官方微博 | 高级检索  
     


%Gra: an SAS macro for generalized redundancy analysis
Authors:Pietro Giorgio Lovaglio
Affiliation:Department of Statistics and Quantitative Methods, University of Bicocca – Milan, Milan, Italy
Abstract:In the framework of redundancy analysis and reduced rank regression, the extended redundancy analysis model managed to account for more than two blocks of manifest variables in its specification. A further extension, the generalized redundancy analysis (GRA), has been recently proposed in literature, with the aim of incorporating external covariates into the model, thanks to a new estimation algorithm that manages to separate all the contributions of the exogenous and external covariates in the formation of the latent composites. At present, software to estimate GRA models is not available. In this paper, we provide an SAS macro, %GRA, to specify and fit structural relationships, with an application to illustrate the use of the macro.
Keywords:Redundancy analysis  SAS macro  alternating least squares  latent components  reduced rank regression
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