Alexander, C. , Stuart-Smith, J. , Neocleous, T. and Evers, L. (2017) Using Chain Graph Models for Structural Inference With an Application to Linguistic Data. In: 32nd International Workshop on Statistical Modelling, Groningen, Netherlands, 03-07 Jul 2017, pp. 270-274.
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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 Proceedings |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Evers, Dr Ludger and Neocleous, Dr Tereza and Alexander, Dr Craig and Stuart-Smith, Professor Jane |
| Authors: | Alexander, C., Stuart-Smith, J., Neocleous, T., and Evers, L. |
| College/School: | College of Arts & Humanities > 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 |
| First Published: | First published in Proceedings of the 32nd International Workshop on Statistical Modelling Volume I: 270-274 |
| Publisher Policy: | Reproduced with the permission of the Authors |
| Related URLs: |
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