Using Chain Graph Models for Structural Inference With an Application to Linguistic Data

Alexander, C. , Stuart-Smith, J. , Neocleous, T. and Evers, L. (2017) Using Chain Graph Models for Structural Inference With an Application to Linguistic Data. 32nd International Workshop on Statistical Modelling, Groningen, Netherlands, 03-07 Jul 2017.

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Abstract

Graphical models provide a visualisation of the conditional dependence structure between variables, making them an attractive inference tool. The improved readability makes this an appealing approach to represent complex model output to non-statisticians. In this paper, we introduce a novel approach using graphical models to visualise the output of a mixed effects model with multivariate response with an application to linguistic data.

Item Type:Conference or Workshop Item
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Alexander, Dr Craig and Evers, Dr Ludger and Stuart-Smith, Professor Jane and Neocleous, Dr Tereza
Authors: Alexander, C., Stuart-Smith, J., Neocleous, T., and Evers, L.
College/School:College of Arts > School of Critical Studies > English Language and Linguistics
College of Science and Engineering > School of Mathematics and Statistics > Statistics
Copyright Holders:Copyright © 2017 The Authors
Publisher Policy:Reproduced with the permission of the Authors
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