Chris Theobald

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BioSS Associate

Biomathematics & Statistics Scotland
JCMB, The King's Buildings,
EDINBURGH, EH9 3JZ, Scotland, UK.

Tel: +44 (0)131 651 7032

Chris Theobald

» DesignSequence Page

I had a joint appointment in BioSS and the School of Mathematics, University of Edinburgh from 2001 to 2011. I now contribute to external projects on potato trials, insect detection in salads and optimum nitrogen fertilization.

Research Interests

My main interest is in the application of Bayesian methods in agriculture. I argue that Bayesian procedures should replace conventional estimative approaches in order to make systematic use of expert knowledge. These are some applications of my ideas.

I am also interested in the design and analysis of visual perception experiments. With Aletta Nonyane and the late Rob Kempton, I have investigated the construction and properties of designs for visual perception experiments which are balanced for carry-over effects. These designs are now being used in neuroimaging. See the DesignSequence Page for more information. We have also developed and applied a Bayesian predictive method for correcting bias in sequences of quantitative visual responses.

With Ayona Chatterjee and Graham Horgan of BioSS, I have considered Bayesian models for dietary data recorded on successive days, particularly components of diet which have very skewed distributions and large proportions of zeros, such as retinol, alcohol and pesticide residues. We have developed a multivariate latent-Gaussian model for the consumption of Iprodione, a widely used pesticide, combining information over several food products on which it is used.

Another interest is in multivariate analysis, particularly discriminant analysis and pattern recognition.

Considering how to exploit the approximate bilateral symmetry of the X-ray images led us to investigate principal component analysis of landmarks from what we call reversible two-dimensional images.

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Journal Publications from 2002

Journal Publications

Recent Papers

(available as pdf)

Staff, Students & Associates

Staff

Research Students

BioSS Associates