Link to my real home page

Please note that this webpage is out of date, following my move to Bristol. My current webpage can be found at http://www.maths.bris.ac.uk/~mazjcr/. You should have been redicrected there automatically.

Awaiting better picture! Dr Jonathan Rougier (Jonty)

Currently:
Lecturer in Statistics
Department of Mathematical Sciences
Durham University

Science Laboratories
South Road
Durham DH1 3LE
tel: +44(0)191 334 3111
email J.C.Rougier@durham.ac.uk


From 1 January:
Lecturer in Statistics
Department of Mathematics
Bristol University

1 February - 31 May:
University Fellow
ISDS, Duke University
Visiting
SAMSI
"[B]egin upon the precept ... that the things we see are to be weighed in the scale with what we know" (Meredith, The Egoist, 1879)

NavigationResearch interests  Current projects  Selected papers  Recent talks  Memberships  (orange background shows links on this page)

Research interests

I study model-based inference for complex systems. I work with directly with experts in the Natural Sciences who want to make better predictions, and I develop the necessary statistical methodology. Rougier (2006) describes a fairly simple inferential approach, applicable to Climate Science.

One key challenge is to devise intuitive and flexible ways to describe the ways in which scientists judge that their models are informative about the underlying system; see, for example, Goldstein and Rougier (2004, 2006b). These will also allow us to unify results from several different models of the same system.

I focus mainly on large problems, where the models can be expensive to evaluate. One approach is to use the model-evaluations to construct an emulator, which is a stochastic representation of the underlying model (which is typically deterministic); see, for example, the talk Introduction to emulators, or the short paper Inference in Ensemble Experiments. Another is to adopt a Bayes Linear approach; see, for example, Goldstein and Rougier (2006a).

Current projects

These projects have a climate focus

  1. The probability of rapid climate change (PI Peter Challoner, National Oceanography Centre, Southampton). Funded under the NERC-RAPID Directed Programme.
  2. RAPID modelling intercomparison project (PI Jonathan Gregory, Reading and the Met Office). Funded under the same programme.
  3. PaleoQUMP: using paleodata to reduce uncertainties in climate prediction (PI Sandy Harrison, Bristol). Funded under the NERC-QUEST Directed Programme.
  4. Met Office. External Expert, funded by DEFRA (TBC).

These projects are more general

  1. Managing uncertainty in complex models (MUCM, PI Tony O'Hagan, Sheffield). Funded by a Basic Technologies grant from the Research Councils UK.
  2. SAMSI year-long program: Development, Assessment and Utilization of Complex Computer Models (Organiser: Jim Berger, Duke University, North Carolina).
  3. Uncertainty Analysis for Random Computer Models (Mentor: Michael Goldstein, Durham). Statistics Mobility Fellowship, funded by the EPSRC.

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Selected papers

NavigationWork in progress  Forthcoming  Statistics  Economics  Other

A more complete list of academic papers is available on my official university webpage.

Work in progress

  • Inference in ensemble experiments. For a Philosophical Transactions Series A special issue on ensemble experiments in climate. Joint work with David Sexton.
  • Lightweight emulators for complex multivariate functions. A step away from the gaussian process gold-standard towards something a bit more `quick and dirty', but with its own quirky elegance.
  • Emulating the sensitivity of the HadAM3 climate model using ensembles from different but related experiments. Building an emulator for a very complicated scalar function. Joint work with David Sexton, James Murphy (both at the Met Office), and Dave Stainforth (Oxford). Available as a pdf file.

Forthcoming

Some Statistics papers

  • J.C Rougier (2005), Probabilistic Leak Detection in Pipelines Using the Mass Imbalance Approach. Journal of Hydraulic Research, 43(5), 556-566.
  • M. Goldstein and J.C. Rougier (2004), Probabilistic formulations for transferring inferences from mathematical models to physical systems, SIAM Journal on Scientific Computing, 26(2), 467-487.
  • J.C. Rougier and M. Goldstein (2001), A Bayesian Analysis of Fluid Flow in Pipelines, Applied Statistics, 50(1), 77-93.
  • P.S. Craig, M. Goldstein, J.C. Rougier and A.H. Seheult (2001), Bayesian forecasting for complex systems using computer simulators, Journal of the American Statistical Association, 96, 717-729.

Some Economics and Finance papers

  • P.R. Holmes and J.C. Rougier (2005), Trading Volume and Contract Rollover in Futures Contracts, Journal of Empirical Finance, 12(2), 317-338.
  • S.C. Parker and J.C. Rougier (2001), Measuring social mobility as unpredictability, Economica, 68, 63-76.
  • B. Hillier and J.C. Rougier (1999), Real business cycles, investment finance and multiple equilibria, Journal of Economic Theory, 86, 100-22.
  • J.C. Rougier (1996), An optimal price index for stock index futures contracts, Journal of Futures Markets, 16, 189-99.

Some other writings

  • J.C. Rougier (2006), Comment on the paper by Haslett et al., Journal of the Royal Statistical Society, Series A, 169(3), pp 432-433.
  • J.C. Rougier (2005), Literate programming for creating and maintaining packages. R News, 5(1), pp 35-39. This number available as a pdf file; a zipped tar file of the example package is also available.
  • J.C. Rougier (2005), A Statistical Approach to System Inference Using Models. Contributed to the floodrisknet.org.uk newsletter. Available as a pdf file (96Kb).
  • J.C. Rougier (2001), Comment on the paper by Kennedy and O'Hagan, Journal of the Royal Statistical Society, Series B, 63, page 453.
  • J.C. Rougier (2001), What's the point of `tensor'?, R News, 1(2), pp 26-27. This number available as a pdf file.

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Recent talks

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Memberships, Committees, Interests

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