Statistics
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Department of Mathematics & Statistics
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Dr Matthew Parry

Office: Science III, room 236
Phone: +64 3 479 7780
Email: mparry@maths.otago.ac.nz


Research interests

Broadly speaking, my two main interests are in statistical modelling and theoretical statistics. To give you some flavour of what I do:

  1. I am working in plant epidemiology and on sensors for agritech applications. The crucial ingredient in both cases is serious modelling of the underlying physical and biological processes. Inference is then carried via MCMC and particle filter tecnhiques.
  2. I also work on scoring rules which are principled ways of assessing probabilistic statements, e.g. forecasting. Scoring rules have important practical application as well as leading into some very nice mathematics.

I am actively looking for Honours and postgraduate students to work on projects in these areas. I value mathematical and computational ability as much as I do statistical background.

Recent Publications

Linear scoring rules for probabilistic binary classification M. Parry, Electronic Journal of Statistics, Vol. 10, No. 1, (2016) 1596-1607.

Efficient recycled algorithms for quantitative trait models on phylogenies G. Hiscott, C. Fox, M. Parry & D. Bryant, Genome Biology and Evolution Vol. 8, Iss. 5 (2016) 1338-1350.

Extensive Scoring Rules M. Parry, Electronic Journal of Statistics, Vol. 10, No. 1 (2016) 1098-1108.

Genome-wide DNA methylation map of human neutrophils reveals widespread inter-individual epigenetic variation A. Chatterjee, P. Stockwell, E. Rodger, E. Duncan, M. Parry, R. Weeks, I. Morison, Scientific Reports 5 (2015) 17328.

Measuring the performance of sensors that report uncertainty A. Martin. T. Molteno, M. Parry, Proc. Electronics New Zealand Conference (2014).

Bayesian inference for an emerging arboreal epidemic in the presence of control M. Parry, G. Gibson, T. Gottwald, M. Irey, T. Gast, and C. Gilligan, Proc. Natl. Acad. Sci. USA 111, 17 (2014) 6258-6262.

Proper local scoring rules M. Parry, A. P. Dawid, and S. Lauritzen, Ann. Statist. 40, 1 (2012), 561-592.

Proper local scoring rules on discrete sample spaces A. P. Dawid, S. Lauritzen, and M. Parry, Ann. Statist. 40, 1 (2012), 593-608.

Informational inefficiency in financial markets D. C. Brody, B. K. Meister, and M. F. Parry, Math Finan Econ (2012) 6:249–259.

Teaching

  • STAT 110 Statistical Methods
  • STAT 341 Generalized Linear Models
  • STAT 442 Big Data
  • STAT 444 Stochastic Processes
  • MATH 4SL Data Mining, Inference and Prediction