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An Axiomatization of Loglinear Models with an Application to the Model-Search Problem

  • Francesco M. Malvestuto
Part of the Lecture Notes in Statistics book series (LNS, volume 112)

Abstract

A good strategy to save computational time in a model-search problem consists in endowing the search procedure with a mechanism of logical inference, which sometimes allows a loglinear model to be accepted or rejected on logical grounds, without resorting to the numeric test. In principle, the best inferential mechanism should based on a complete axiomatization of loglinear models. We present a (probably incomplete) axiomatization, which can be translated into a graphical inference procedure working with directed acyclic graphs, and show how it can be applied to find an efficient solution to the model-search problem.

Keywords

Directed Acyclic Graph Inference Rule Conditional Independence Universal Model Loglinear Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York, Inc. 1996

Authors and Affiliations

  • Francesco M. Malvestuto

There are no affiliations available

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