Jonathan (Jonty) Rougier's homepage

Senior Lecturer in Statistics, Department of Mathematics, University of Bristol, UK.

• Fairly recent photo
• Contact details

1. SAPPUR: scoping study on risk and uncertainty in natural hazards. This £130k scoping study will take place over June to October 2009 and aims to provide an overview of tools and methodologies for the analysis, propagation and communication of uncertainty and risk within natural hazards science. BRISK will be working with the rest of the UK scientific community and international experts to provide the background and recommendations to help NERC develop a world-class research programme.

2. MUCM. "The MUCM project will develop a technology that is capable of addressing all sources of uncertainty in model predictions and to quantify their implications efficiently, even in the most complex models. It has the potential to revolutionise scientific debate by resolving the contradictions in competing models. It will also have a radical effect on everyday modelling and model usage by making the uncertainties in model outputs transparent to modellers and end users alike." Funded by Research Councils UK.

3. UK Met Office. External expert to advise on uncertainty, particularly with respect to the QUMP project and UKCIP08. Funded by Defra.

   QUMP stands for Quantifying Uncertainty in Model Predictions: it is an experiment run by the scientists in the Met Office, to look at the effect of perturbing the parameters of the HadCM3 climate model. A complementary project is run by climateprediction.net.

4. PalaeoQUMP: "PalaeoQUMP aims to constrain climate sensitivity [...] using a wider range of derived climate observations from the geological past (reconstructions from sediments and geomorphological changes for the Last Glacial Maximum and the mid-Holocene period), to evaluate climate model predictions generated using the same series of simulations as QUMP produced for the modern climate." Funded by NERC QUEST.

5. THC MIP. This is a project to compare the way in which different ocean models represent the thermohaline circulation (THC). A crucial question is the degree to which we can capture this very complicated phenomenon with quite simple models. Funded by NERC RAPID.

6. CASE studentship: Estimating and reducing the uncertainty in the future behaviour of the Greenland ice sheet.

Back to the top

In submission

1. J.C. Rougier and M. Kern (2010), Predicting Snow Velocity in Large Chute Flows Under Different Environmental Conditions.

   Assimilating observations, model predictions, and expert judgements into a prediction for snow behaviour. Joint work with Martin Kern at the BFW Institute for Natural Hazards and Alpine Timberline. Revised version, available as a pdf file (revised 8 Feb, 2010).

2. M. Goldstein, L. House, and J.C. Rougier (2008), Assessing model discrepancy using a multi-model ensemble.

   How to combine an ensemble of model-evaluations with observations, where we have them, to assess the mean vector and variance matrix of the discrepancy between our model and reality. Uses second-order exchangeability as the statistical model for the ensemble, so does not insist on model 'independence', but allows for shared biases in models. Has an illustration using climate models from the IPCC AR4 multi-model ensemble. Available as a pdf file, includes some colour plots (3.3MB). Slides available (6MB).

Promised

3. J.C. Rougier, D. Cameron, N. Edwards (2008), Precalibrating an intermediate complexity climate model.

   A more robust (but less powerful) approach to ruling out regions of model parameter-space, using the 'implausibility' approach. Computationally intensive but inferentially (relatively) undemanding.

Other people

4. I. Scheel, P. Green, and J.C. Rougier (2008), Identifying influential model choices in Bayesian hierarchical models.

   A graphical approach to identifying potential misspecification in the tails of hierarchical models expressed as chain graphs. Available as a pdf file, with supplementary information.

Back to the top

J.C. Rougier, S. Guillas, A. Maute, A.D. Richmond (2009), Expert Knowledge and Multivariate Emulation: The Thermosphere-Ionosphere Electrodynamics General Circulation Model (TIE-GCM), Technometrics, 51(4), 414-424. doi:10.1198/TECH.2009.07123

M. Goldstein and J.C. Rougier (2009), Reified Bayesian Modelling and Inference for Physical Systems, Journal of Statistical Planning and Inference, 139(3), 1221-1239. doi:10.1016/j.jspi.2008.07.019 With discussion and rejoinder.

J.C. Rougier (2008), Efficient Emulators for Multivariate Deterministic Functions, Journal of Computational and Graphical Statistics, 17(4), 827-843. doi:10.1198/106186008X384032. R package OPE_0.8.tar.gz.

J.C. Rougier (2008), Discussion of 'Inferring Climate System Properties Using a Computer Model', by Sanso et al, Bayesian Analysis, 3(1), 45-56. DOI:10.1214/08-BA301B

M. Goldstein and J.C. Rougier (2006), Bayes Linear Calibrated Prediction for Complex Systems, Journal of the American Statistical Association, 101 (no. 475), 1132-1143.

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.

I. MacPhee, J.C. Rougier and G. Pollard (2004), Server Advantage in Tennis Matches, Journal of Applied Probability, 41(4), 1182-1186.

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.

Other science

S. Guillas, J.C. Rougier, A. Maute, A.D. Richmond, and C.D. Linkletter (2009), Bayesian calibration of the Thermosphere-Ionosphere Electrodynamics General Circulation Model (TIE-GCM), Geoscientific Model Development, 2, 137-144. Available online.

M. Crucifix and J.C. Rougier (2009), On the use of simple dynamical systems for climate predictions: A Bayesian prediction of the next glacial inception. The European Physics Journal - Special Topics, 174(1), 11-31. DOI:10.1140/epjst/e2009-01087-5

J.C. Rougier, D.M.H. Sexton, J.M. Murphy, and D. Stainforth (2009), Analysing the climate sensitivity of the HadSM3 climate model using ensembles from different but related experiments. Journal of Climate, 22(13), 3540-3557. DOI:10.1175/2008JCLI2533.1

J.C.Rougier and D.M.H. Sexton (2007), Inference in Ensemble Experiments, Philosophical Transactions of the Royal Society, Series A, 365, 2133-2143.

J.C. Rougier (2007), Probabilistic Inference for Future Climate Using an Ensemble of Climate Model Evaluations, Climatic Change, 81, 247-264. DOI:10.1007/s10584-006-9156-9

J.C Rougier (2005), Probabilistic Leak Detection in Pipelines Using the Mass Imbalance Approach. Journal of Hydraulic Research, 43(5), 556-566.

M. van Oijen, J.C. Rougier and R. Smith (2005), Bayesian Calibration of Process-Based Forest Models: Bridging the Gap Between Models and Data, Tree Physiology, 25, 915-927.

Economics and Finance

S.C. Parker and J.C. Rougier (2007), The Retirement Behaviour of the Self-Employed in Britain, Applied Economics, 39(6), 697-713.

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 (1997), A Simple Necessary Condition for Negativity in the Almost Ideal Demand System with the Stone Price Index, Applied Economics Letters, 4, 97-9.

J.C. Rougier (1996), An Optimal Price Index for Stock Index Futures Contracts, Journal of Futures Markets, 16, 189-99.

J.C. Rougier (1993), The Impact of Margin-Traders on the Distribution of Daily Stock Returns: The London Stock Exchange, Applied Financial Economics, 3, 325-8.

Non-peer-reviewed

J.C. Rougier (2009), Notes on statistical modelling for complex systems, ver. 0.5, unpublished. Available as a pdf file. Please note the version number: this document is still evolving.

J.C. Rougier (2008), Climate change detection and attribution, ISBA bulletin, 15(4), 3-6. Available on-line.

J.C. Rougier (2008), Formal Bayes Methods for Model Calibration with Uncertainty, in K. Beven and J. Hall (eds), Applied Uncertainty Analysis for Flood Risk Management, Imperial College Press / World Scientific. Draft version available as a pdf file.

J.C. Rougier (2006), Comment on the paper by Haslett et al., Journal of the Royal Statistical Society, Series A, 169(3), 432-433.

J.C. Rougier (2005), Literate Programming for Creating and Maintaining Packages. R News, 5(1), 35-39.

J.C. Rougier (2004), Comment on the paper by Murphy et al. Nature did not want to publish this comment, but I think it says some useful things. Available as a pdf file.

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), 26-27.

Back to the top

• Uncertainty and risk in natural hazards, Nottingham, Nov 2009. Slides available.
• Introduction to computer experiments, and the challenges of expensive models, RSS Statistical Computing Section, Bath, October 2009. Slides available.
• Quantifying uncertainty in probability of exceedence (PE) curves, NERC/KTN workshop on Catastrophe modelling for natural hazard impact, Lloyd's, London, Oct 2009. Slides available and also R code for the pictures.
• Emulator-based simulator calibration for high-dimensional data, JCGS session, JSM-2009, Washington DC, Aug 2009. Slides available.
• The What, Why, and How of Multivariate Emulation, Spring Research Conference On Statistics in Industry and Technology, Vancouver, May 2009. Slides available.
• Simple models for glacial cycles, Bath Institute for Complex Systems, Feb 2009. Slides available.
• Statistical calibration of physical models, WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland, Dec 2008. Slides available.

• Fellow, Royal Statistical Society, 1997 -, Environmental Statistics Section, 2005 -
• International Society for Bayesian Analysis (ISBA), 2001 -
• Associate Editor, Applied Statistics (Journal of the Royal Statistical Society, Series C), 2009 -
• Reviewer, European Research Council, 2009 -

Upversion (vb, with obj.). To take something, typically a software program, to the next version. Example (from the web) "To get our nightly builds running again, I need to upversion the plugins."

Back to the top