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Research

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Professor Michael Goldstein

Personal web page

Telephone: +44 (0) 191 33 43065
Room number: CM207
Leader of Work Package 3 in Tipping Points Research Project
Telephone: +44 (0) 191 33 42365

Contact Professor Michael Goldstein (email at michael.goldstein@durham.ac.uk)

Research Groups

Department of Mathematical Sciences

Research Interests

  • Statistics

Publications

Books: authored

Books: sections

  • Goldstein, M. (2011). External Bayesian analysis for computer simulators. In BAYESIAN STATISTICS 9. Bernardo, J.M., Bayarri, M.J., Berger, J.O., Dawid, A.P., Heckerman, D., Smith, A.F.M. & West, M. Oxford University Press.
  • Cumming, J. & Goldstein, M. (2009). Bayes Linear Uncertainty Analysis for Oil Reservoirs Based on Multiscale Computer Experiments. In The Oxford Handbook of Applied Bayesian Analysis. O'Hagan, & West,A.M. Oxford University Press. 241-270.
  • Craig, P.S., Goldstein, M., Seheult, A.H. & Smith, J.A. (1997). Pressure matching for hydrocarbon reservoirs: a case in the use of Bayes linear strategies for large computer experiments (and discussion). In Case studies in Bayesian Statistics. Gatsonis et al New York: Springer-Verlag. III: 37-93.

Edited works: conference proceedings

  • Craig, P.S., Smith, J.A., Goldstein, M. & Seheult, A.H. (1995). Matching hydrocarbon reservoir history - a Bayes linear approach. Third International Applied Statistics in Industry Conference.

Edited works: contributions

  • Coolen, F. P., Goldstein, M. & Wooff, D. A. (2005). Using Bayesian statistics to support testing of software systems. In Proceedings of the 16th Advances in Reliability Technology Symposium. Andrews, J. 109-121.
  • Coolen, F. P. A., Goldstein, M. & Wooff, D. A. (2003). Project viability assessment for support of software testing via Bayesian graphical modelling. In Safety and Reliability. Bedford & van Gelder Lisse: Swets & Zeitlinger. 417-422.

Journal papers: academic

  • Rougier, J., Goldstein, M. & House, L. (2013). "Second-order exchangeability analysis for multi-model ensembles. Journal of the American Statistical Association 108(503): 852-863.
  • Williamson, D., Goldstein, M. & Blaker, A. (2012). Fast Linked Analyses for Scenario-based Hierarchies. Journal of the Royal Statistical Society, Series C: Applied Statistics 61(5): 665-691.
  • Williamson, D & Goldstein, M (2011). Bayesian Policy Support for Adaptive Strategies using Computer Models for Complex Physical Systems. Journal of the Operational Research Society
  • Farrow, M. & Goldstein, M. (2010). Sensitivity of decisions with imprecise utility trade-off parameters using boundary linear utility. International Journal of Approximate Reasoning 51: 1100–1113.
  • Randell, D., Goldstein, M., Hardman, G. & Jonathan P. (2010). Bayesian linear inspection planning for large-scale physical systems. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 224(4): 333-345.
  • Vernon, I., Goldstein, M. & Bower, R. (2010). Galaxy Formation: a Bayesian Uncertainty Analysis. Bayesian analysis 5: 619-670.
  • Farrow, M. & Goldstein, M. (2009). Almost-Pareto decision sets in imprecise utility hierarchies. Journal of Statistical Theory and Practice 3: 137-155.
  • Goldstein, M. & Rougier, J.C. (2009). Reified Bayesian modelling and inference for physical systems. Journal of Statistical Planning and Inference 139(3): 1221-1239.
  • Cumming, J. & Goldstein, M. (2009). Small Sample Bayesian Designs for Complex High-Dimensional Models Based on Information Gained Using Fast Approximations. Technometrics 51(4): 377-388.
  • Goldstein, M. & Seheult, A.H. (2008). Prior viability assessment for Bayesian analysis, Journal of Statistical Planning and Inference. Journal of Statistical Planning and Inference 138: 1271-1286
  • Goldstein, M. (2006). Subjective Bayesian analysis: principles and practice. Bayesian Analysis 1: 403-420.
  • Goldstein, M. & Rougier, J.C. (2006). Bayes Linear Calibrated Prediction for Complex Systems. Journal of the American Statistical Association 101(475): 1132-1143.
  • Farrow, M. & Goldstein, M. (2006). Trade-off sensitive experimental design: a multicriterion, decision theoretic, Bayes linear approach. Journal of Statistical Planning and Inference 136(2): 498-526.
  • Goldstein, M. & Rougier, J.C. (2005). Probabilistic formulations for transferring inferences from mathematical models to physical systems. SIAM journal on scientific computing. SIAM journal on scientific computing 26: 467-487.
  • Goldstein, M. & Shaw S. (2004). Bayes linear kinematics and Bayes linear Bayes Graphical Models. Biometrika 91(2): 425-446.
  • Shaw, S.C., Goldstein, M., Munro, M. & Burd, E. (2003). Moral dominance relations for program comprehension. IEEE Transactions on Software Engineering 29(9): 851-863.
  • Wooff, D. A., Goldstein, M. & Coolen, F. P. A. (2002). Bayesian Graphical Models for Software Testing. IEEE Transactions on Software Engineering 28(5): 510-525.
  • Rougier, J.C. & Goldstein, M. (2001). A Bayesian Analysis of Fluid Flow in Pipelines. Applied statistics a journal of the Royal Statistical Society 50(1): 77-93.
  • Goldstein, Michael (2001). Avoiding foregone conclusions: geometric and foundational analysis of paradoxes of finite additivity. Journal of Statistical Planning and Inference 94(1): 73-87.
  • Craig, P. S., Goldstein, M., Rougier, J. C. & Seheult, A. H. (2001). Bayesian forecasting for complex systems using computer simulators. Journal of the American Statistical Association 96(454): 717-729.
  • Coolen, F.P.A., Goldstein, M. & Munro, M. (2001). Generalized partition testing via Bayes linear methods.
  • Coolen, F. P. A., Goldstein M. & Munro, M. (2001). Generalized partition testing via Bayes linear methods. Information and software technology 43(13): 783-793.
  • Rees, K., Coolen, F. P. A., Goldstein, M. & Wooff, D. A. (2001). Managing the uncertainties of software testing: a Bayesian approach. Quality and Reliability Engineering International 17: 191-203.
  • Goldstein, M. & Wilkinson, D.J. (2001). Restricted prior inference for complex uncertainty structures. Annals of Mathematics and Artificial Intelligence 32: 315-334.
  • Goldstein, M. & Wilkinson, D.J. (2000). Bayes linear analysis for graphical models: the geometric approach to local computation and interpretive graphics. Statistics and Computing 10: 311-324.
  • Wooff, D. A. & Goldstein, M. (2000). Bayes Linear Methods III - Analysing Bayes linear influence diagrams and Exchangeability in [B/D]. Journal of Statistical Software 5(2).
  • Goldstein, M. & Kotz, S. et al (1999). Bayes linear analysis.
  • Goldstein, M. & Williams, D.R. (1999). Graphical diagnostics for the Bayes linear analysis of hierarchical linear models, with applications to educational data.
  • Goldstein, M. & Shaw, S.C. (1999). Simplifying complex designs: Bayes linear experimental design for grouped multivariate exchangeable systems.
  • Goldstein, M. & Wooff, D. A. (1998). Adjusting exchangeable beliefs. Biometrika 85: 39-54.
  • Craig, P.S., Goldstein, M., Seheult, A.H. & Smith, J.A. (1998). Constructing partial prior specifications for models of complex physical systems.
  • Goldstein, M. & Wooff, D. A. (1997). Choosing samples sizes in balanced experimental designs: a Bayes linear approach. Journal of the Royal Statistical Society, Series D: The Statistician 46: 167-183.
  • Goldstein, M., Farrow, M. & Spiropoulos, T. (1997). Developing a Bayes linear decision support system for a brewery. The Practice of Bayesian Analysis, eds. S. French and J. Q. Smith, Edward Arnold 71-106.
  • Goldstein, M (1997). Prior inferences for posterior judgements.
  • Goldstein, M & Wilkinson, D.J. (1996). Bayes Linear Adjustment for Variance Matrices.
  • Goldstein, M, Craig, P.S., Seheult, A.H. & Smith, J.A. (1996). Bayes Linear Strategies for Matching Hydrocarbon Reservoir History and discussion.
  • Goldstein M & A. O'Hagan (1996). Bayes linear sufficiency and systems of expert posterior assessments. Journal of the Royal Statistical Society, Series B 58: 301-316.
  • Goldstein, M & Farrow, M. (1996). Diagnostic Geometry for Bayes Linear Prediction Systems.
  • Goldstein, M. & Wooff, D. A. (1995). Bayes linear computation: concepts, implementation and programming environment. Statistics and Computing 5: 327-341.
  • Goldstein, M. (1994). Belief revision: subjectivist principles and practice in Logic and Philosophy of Science in Uppsala, eds. Prawitz, D. and Westerstahl, D.
  • Goldstein, M. (1994). Revising Exchangeable Beliefs: Subjectivist foundations for the inductive argument in.
  • Goldstein, M. & Wooff, D. A. (1994). Robustness measures for Bayes linear analysis (with discussion). Journal of Statistical Planning and Inference 40: 261-277.

Other media: research

Supervises

Selected Grants

  • 2012: Calibration and analysis of complex inidvidual.... (£39529.24 from MRC)
  • 2008: JOINT INVERSION WITH BAYESIAN ANALYSIS (£182333.26 from Industry Technology Facilitator)