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Steven Miller

Department of Statistics
Academic Staff >> Lecturers
Steven Miller (Dr)

BSc(Hons), BCom, PhD Auck, A.T.C.L.


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Personal Description
Steven joined the Department of Statistics as a lecturer in 2009. He completed his PhD at the University of Auckland, focussing on an ecological application of population genetics to investigate the invasion dynamics of introduced rats on New Zealand islands. He then undertook post-doctoral research at Trinity College in the University of Dublin, designing a methodology to incorporate information from disparate sources characterising a common process. A particular application of this research was to reconstruct the spread of the Neolithic culture across Europe based on archaeological, genetic and linguistic evidence.

Research Interests
Research Interests Ecological Statistics; Population Genetics; Stochastic Dynamics I am particularly interested in the application of statistics in the areas of ecology and population genetics. New Zealand is home to an abundance of species found nowhere else in the world, many of which are threatened by the introduction of exotic pests. Generating knowledge in the field of ecological statistics is my contribution to the preservation of our native species. As part of my doctoral research, I became interested in estimating parameters governing the spread of populations using genetic data. This, combined with an amateur interest in archaeology, was an important thread in the work I performed while in Dublin. All my work has dealt with high degrees of uncertainty, and access to specialist knowledge, which has proven ideal for the application of statistics following the Bayesian approach. While in Dublin I was introduced to means of performing analysis when the likelihood of observed data given a model is intractable, such as using Approximate Bayesian Computation (ABC). ABC is notoriously inefficient however, so I would like to find a middle-ground between adopting a standard parameterised model and using a simulation-based approach for parameter estimation.

Publications - 2012

Articles in Professional Journals

    Paul, W.J., Hamilton , D.P., Ostrovsky, I, Miller, S.D., Zhang, A., and Muraoka, K. (2012) Catchment land use and trophic state impacts on phytoplankton composition: a case study from the Rotorua lakes district, New Zealand Hydrobiologia, The International Journal of Aquatic Service, Springer Science+Business Media, 698, 133-146.

Publications - 2011

Articles in Refereed Journals

    Abell, J.M., Ozkundakci, D., Hamilton, D.P., and Miller, S.D. (2011) Relationships between land use and nitrogen and phosphorus in New Zealand lakes Marine & Freshwater Research, 62 (2), 162-175

Ed. Vols. of Conference Proceedings

    Fewster, R.M., Miller, S.D., and Ritchie, J. (2011) DNA profiling - a management tool for rat eradication

Edited Volumes of Conference Proceedings

    Fewster, R.M., Miller, S.D., and Ritchie, J. (2011) DNA profiling - a management tool for rat eradication Island Invasives: Eradication and Management (eds C.R. Veitch, M.M. Clout, and D.R. Towns), Proceedings of the International conference on Island Invasives, 426-431.

Publications - 2010

Conference Presentations

    Miller, S.D. (2010) Characterising the spread of Neolithic culture across Europe Australian Statistical Conference, Statistics in the West: Understanding our world. 6-10 December 2010 Fremantle, Western Australia

      The Neolithic era, the last major sub-division of the Stone age, began about 11,000 years ago when agriculture was developed in the Middle East. From there, Neolithic culture spread into Europe, with the era ending in Europe about 5,000 years ago, upon the widespread adoption of metal tools. The spread of Neolithic culture could have resulted from a migration of people, a diffusion of ideas, or more likely a combination of the two. Residual signals from this transition across Europe might still be found in ancient and potentially modern patterns of genetic and linguistic variation, as well as in the archaeological record. We are attempting to formally model this process by combining evidence from these multiple sources in association with a non-trivial diffusion model across a landscape. This has required the development of a method involving indirect inference to extract information from a series of computer simulations in order to estimate distributions for the diffusion parameters of interest.
  2007 FCMS. The University of Waikato - Te Whare Wananga o Waikato