Generalized bi-additive modelling for categorical data
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.
Year of publication: |
2004-03-17
|
---|---|
Authors: | Groenen, Patrick ; Koning, Koning, A.J. |
Institutions: | Faculteit der Economische Wetenschappen, Erasmus Universiteit Rotterdam |
Saved in:
freely available
Extent: | application/pdf |
---|---|
Series: | Econometric Institute Research Papers. - ISSN 1566-7294. |
Type of publication: | Book / Working Paper |
Notes: | The text is part of a series RePEc:ems:eureir Number EI 2004-05 |
Source: |
Persistent link: https://www.econbiz.de/10010837777
Saved in favorites
Similar items by person
-
Optimal Scaling of Interaction Effects in Generalized Linear Models
Groenen, Patrick, (2007)
-
A new model for visualizing interactions in analysis of variance
Groenen, Patrick, (2004)
-
Confidence intervals for maximal reliability of probability judgments
Franses, Philip Hans, (2007)
- More ...