Reduced-Rank VGLMs

  • Thomas W. Yee
Part of the Springer Series in Statistics book series (SSS)


This chapter looks at a subclass of VGLMs called Reduced-Rank VGLMs (RR-VGLMs). They are built on the idea of latent variables, and are the same as VGLMs except some of their constraint matrices are estimated. RR-VGLMs have with interesting properties and applications. It is a dimension-reduction method, e.g., when applied to the multinomial logit model it leads to the stereotype model. Another related class of models is row–column interaction models (RCIMs), and two-parameter RR-VGLMs are described in this chapter. Some applications mentioned here and/or developed elsewhere include quasi-variances and indirect gradient analysis.


Latent Variable Linear Discriminant Analysis Latent Trait Constraint Matrice Structural Zero 
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Copyright information

© Thomas Yee 2015

Authors and Affiliations

  • Thomas W. Yee
    • 1
  1. 1.Department of StatisticsUniversity of AucklandAucklandNew Zealand

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