Applied Research

Geoforensics and Information Management for crime Investigation (GIMI)

Project Staff - Mark Brewer

Mark BrewerDr. Mark John Brewer BSc, PhD.
Biomathematics and Statistics Scotland (BioSS),
BioSS Office,
The Macaulay Land Use Research Institute,
Craigiebuckler,
ABERDEEN,
AB15 8QH.

Tel: +44 (0)1224 395000 X2072
Fax: +44 (0)1224 312147

M.Brewer@bioss.ac.uk
www.bioss.ac.uk
http://www.bioss.sari.ac.uk/~markb/

Current research activities

Mark is a senior Statistician in BioSS Environmental Modelling Unit at Macaulay Land Use Research Institute.  His current activities include aspects of Spatial and temporal modelling ( http://www.bioss.sari.ac.uk/research/spatio.html )

Prior to appointment with BioSS, Mark worked for eight years as statistical researcher, consultant and lecturer in University mathematics and statistics departments. His research concentrated on computational statistics, with emphasis on Bayesian statistics and Markov chain Monte Carlo methodology. The experience gained through this research is put to good use in a number of collaborative projects with Macaulay Land Use Research Institute staff, including novel applications of Bayesian statistics. Recent research work includes a spatial analysis on the grazing impacts of herbivores in upland Scotland and, with a PhD student, a study of the spatial movement patterns of sparrowhawks. His consultancy work at the Institute covers additional applications such as water chemistry and plant chemistry. More recently, Mark has been working in the area of forensic statistics on the SoilFit project coordinated from the Macaulay Land Use Research Institute.

Publications

Brewer M.J. (2000) A Bayesian model for local smoothing in kernel density estimation. Statistics and Computing, 10, 295-307.

Brewer, M.J., SOULSBY, C. and DUNN, S.M. (2002) A Bayesian model for compositional data analysis. In: COMPSTAT 2002 Proceedings, Hardle, W. & Ronz, B. (Eds.). Physica-Verlag, Heidelberg, pp. 105-110.

Brewer, M.J., ELSTON, D.A. & GREEN, R. (2002) Scoping study to consider the options for a cost effective, statistically-robust otter surveillance programme in Scotland: 2003/2004. Contract Report for SNH (41/6).

Brewer, M.J. (2003) Discretisation for inference on Bayesian mixture models. Statistics and Computing, 13, 209-219.

Brewer, M.J., ELSTON, D.A., & NOLAN, A.J. (2003) Spatial mixture models for ordinal responses: grazing impacts in Scotland, UK. In: Proceedings of the 18th International Workshop on Statistical Modelling, Verbeke, G., Molenberghs, G., Aerts, M., & Fieuws, S. (Eds.). Leuven, Katholieke Universiteit Leuven, pp. 51-56.