http://hdl.handle.net/1765/1194
series: EI 2004-05

Generalized bi-additive modelling for categorical data


Research Paper
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Generalized linear modelling (GLM) is a versatile technique, which may be viewed as a generalization of well-known techniques such as least squares regression, analysis of variance, loglinear modelling, and logistic regression. In may applications, low-order interaction (such as bivariate interaction) terms are included in the model. However, as the number of categorical variables increases, the total number of low-order interactions also increases dramatically. In this papaer, we propose to constrain bivariate interactions by a bi-additive model which allows a simple graphical representation in which each category of every variable is represented by a vector.





Automatically Extracted Terms
  • interaction
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  • lung cancer
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  • bi-additive
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  • bivariate interactions
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  • smoking
  • number
  • rank p model
  • taiyuan
  • matrix
  • bivariate
  • table
  • modelling
  • dimension
  • china