Research Related Links
Research Areas
Conferences & Presentations
Publications
Software
Teaching
Social
Science Statistics 1 (SSS1)
Statistics 1C (S1C)
Multivariate Statistics 3
Level 3 Co-ordinator
Level 3 General Information
Resources & Links
LaTeX Primer by D. R. Wilkins
R Primer by Christopher Green
Dissertation
Download my PhD. Dissertation [PDF]
Curriculum Vitae
Download my CV [PDF]
Other Links
School
of Mathematics and Statistics Webpage
Statistics Subject Webpage
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Research Areas
Unsupervised Learning
• Extending the current mixture modelling framework for clustering (of which model-based clustering and latent class analysis are examples) to allow for dependence between different types of variables.
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• Exploring variable selection in the context of model-based clustering and latent class analysis.
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• Estimation of student skill set profiles and fitting different clustering methods to the resulting restricted sample space.
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• Combining mixture model density estimation with linkage clustering methods via a general density-based similarity measure to help in visualisation of cluster structure in high dimensional data, exploration of hierarchical cluster structure and modelling of complex cluster shapes.
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Semi-supervised Learning
• Semi-supervised techniques involve using information from data without outcome information to help in the estimation of models for data with outcome information. This is particularly important when only a small proportion of data with known outcomes are available. My interests lie in the following areas: |
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• Exploring variable selection in the context of supervised and semi-supervised model-based discriminant analysis and latent class analysis.
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• Adapting model-based discriminant analysis techniques in combination with model-based clustering methods into semi-supervised classification rules.
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Areas of Application
• Educational testing, microarray studies, spectroscopic data, medical research, cognitive diagnosis, food authenticity studies, general social survey data, housing prices
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Current Collaborators
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