Staff profile
Overview
https://apps.dur.ac.uk/biography/image/1427
Affiliation | Telephone |
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Professor in the Department of Mathematical Sciences |
Research interests
- Bayesian Statistics
Esteem Indicators
- 2000: 'Committee Duties': Member of electoral college of EPSRC and Member of board of directors of the International Society for Bayesian Analysis
Publications
Authored book
- Tipping Points: Modelling Social Problems and HealthBissell, J., Caiado, C., Curtis, S., Goldstein, M., & Straughan, B. (2015). Tipping Points: Modelling Social Problems and Health. Wiley. https://doi.org/10.1002/9781118992005
- Bayes Linear Statistics: Theory and MethodsGoldstein, M., & Wooff, D. (2007). Bayes Linear Statistics: Theory and Methods. John Wiley and Sons.
Chapter in book
- Foundations for temporal reasoning using lower previsions without a possibility spaceTroffaes, M. C., & Goldstein, M. (2022). Foundations for temporal reasoning using lower previsions without a possibility space. In T. Augustin, F. Gagliardi Cozman, & G. Wheeler (Eds.), Reflections on the Foundations of Probability and Statistics: Essays in Honor of Teddy Seidenfeld (1st ed., pp. 69-96). Springer Verlag. https://doi.org/10.1007/978-3-031-15436-2_4
- Heart Online Uncertainty and Stability EstimationCaiado, C., Hickey, G., Grant, S., Goldstein, M., Markarian, G., McCollum, C., & Bridgewater, B. (2015). Heart Online Uncertainty and Stability Estimation. In J. Bissell, C. Caiado, S. Curtis, M. Goldstein, & B. Straughan (Eds.), Tipping Points: Modelling Social Problems an Health. Wiley. https://doi.org/10.1002/9781118992005.ch5
- External Bayesian analysis for computer simulatorsGoldstein, M. (2011). External Bayesian analysis for computer simulators. In J. Bernardo, M. Bayarri, J. Berger, A. Dawid, D. Heckerman, A. Smith, & M. West (Eds.), BAYESIAN STATISTICS 9. Oxford University Press.
- Bayes Linear Uncertainty Analysis for Oil Reservoirs Based on
Multiscale Computer ExperimentsCumming, J., & Goldstein, M. (2009). Bayes Linear Uncertainty Analysis for Oil Reservoirs Based onMultiscale Computer Experiments. In A. O’Hagan & M. West (Eds.), The Oxford Handbook of Applied Bayesian Analysis (pp. 241-270). Oxford University Press.
- Using Bayesian statistics to support testing of software systems.Coolen, F., Goldstein, M., & Wooff, D. (2005). Using Bayesian statistics to support testing of software systems. In J. Andrews (Ed.), Proceedings of the 16th Advances in Reliability Technology Symposium (pp. 109-121).
- Project viability assessment for support of software testing via Bayesian graphical modellingCoolen, F., Goldstein, M., & Wooff, D. (2003). Project viability assessment for support of software testing via Bayesian graphical modelling. In T. Bedford & P. van Gelder (Eds.), Safety and Reliability (pp. 417-422). Swets & Zeitlinger.
- Bayes linear analysis.Goldstein, M. (1999). Bayes linear analysis. In S. Kotz, C. Read, & D. Banks (Eds.), Encyclopaedia of Statistical Sciences Update Volume 3 (pp. 29-34). Wiley.
- Graphical diagnostics for the Bayes linear analysis of hierarchical linear models, with applications to educational data.Goldstein, M., & Williams, D. (1999). Graphical diagnostics for the Bayes linear analysis of hierarchical linear models, with applications to educational data. In J. Bernardo, J. Berger, A. Dawid, & A. Smith (Eds.), Bayesian Statistics 6. Proceedings of the Sixth Valencia International Meeting. (pp. 859-867). Oxford University Press.
- Simplifying complex designs : Bayes linear experimental design for grouped multivariate exchangeable systems.Goldstein, M., & Shaw, S. (1999). Simplifying complex designs : Bayes linear experimental design for grouped multivariate exchangeable systems. In J. Bernardo, J. Berger, A. Dawid, & A. Smith (Eds.), Bayesian Statistics 6. Proceedings of the Sixth Valencia International Meeting (pp. 839-848). Oxford University Press.
- Developing a Bayes linear decision support system for a breweryGoldstein, M., Farrow, M., & Spiropoulos, T. (1997). Developing a Bayes linear decision support system for a brewery. In S. French & J. Smith (Eds.), The Practice of Bayesian Analysis. (pp. 71-106). Edward Arnold.
- Pressure matching for hydrocarbon reservoirs: a case in the use of Bayes linear strategies for large computer experiments (and discussion)Craig, P., Goldstein, M., Seheult, A., & Smith, J. (1997). Pressure matching for hydrocarbon reservoirs: a case in the use of Bayes linear strategies for large computer experiments (and discussion). In G. et al (Ed.), Case studies in Bayesian Statistics (pp. 37-93). Springer-Verlag.
- Prior inferences for posterior judgements.Goldstein, M. (1997). Prior inferences for posterior judgements. In M. Chiara, K. Doets, D. Mundici, & J. Benthem (Eds.), Structure and norms in Science : Volume Two of the Tenth International Congress of Logic, Methodology and Philosophy of Science, Florence, August 1995. (pp. 55-71). Springer Netherlands. https://doi.org/10.1007/978-94-017-0538-7_4
- Bayes linear strategies for matching hydrocarbon reservoir history and discussion.Goldstein, M., Craig, P., Seheult, A., & Smith, J. (1996). Bayes linear strategies for matching hydrocarbon reservoir history and discussion. In J. Bernardo, J. Berger, A. Dawid, & A. Smith (Eds.), Bayesian Statistics 4. Proceedings of the Fourth Valencia International Meeting: Dedicated to the memory of Morris H. DeGroot, 1931-1989: April 15-20, 1991 (pp. 69-95). Oxford University Press.
- Revising Exchangeable Beliefs: Subjectivist foundations for the inductive argument.Goldstein, M. (1994). Revising Exchangeable Beliefs: Subjectivist foundations for the inductive argument. In P. Freeman & A. Smith (Eds.), Aspects of uncertainty: a tribute to D.V. Lindley. (pp. 201-222). John Wiley and Sons.
- Belief revision : subjectivist principles and practice.Goldstein, M. (1994). Belief revision : subjectivist principles and practice. In D. Prawitz & D. Westerstahl (Eds.), Logic and Philosophy of Science in Uppsala (pp. 117-130). Springer Netherlands. https://doi.org/10.1007/978-94-015-8311-4_8
- Diagnostic geometry for Bayes linear prediction systems.Goldstein, M., & Farrow, M. (1992). Diagnostic geometry for Bayes linear prediction systems. In J. Bernardo, J. Berger, A. Dawid, & A. Smith (Eds.), Bayesian Statistics 4. Proceedings of the Fourth Valencia International Meeting: Dedicated to the memory of Morris H. DeGroot, 1931-1989: April 15-20, 1991. (pp. 561-568). Oxford University Press.
- Bayes linear adjustment for variance matrices.Goldstein, M., & Wilkinson, D. (1992). Bayes linear adjustment for variance matrices. In J. Bernardo, J. Berger, A. Dawid, & A. Smith (Eds.), Bayesian statistics 4. Proceedings of the Fourth Valencia International Meeting: Dedicated to the memory of Morris H. DeGroot, 1931-1989: April 15-20, 1991 (pp. 791-799). Oxford University Press.
Conference Paper
- Accounting for Model Discrepancy in Uncertainty Analysis by Combining Numerical Simulation and Bayesian Emulation TechniquesFormentin, H. N., Vernon, I., Goldstein, M., Caiado, C., Avansi, G., & Schiozer, D. (2020, September). Accounting for Model Discrepancy in Uncertainty Analysis by Combining Numerical Simulation and Bayesian Emulation Techniques. Presented at ECMOR XVII. https://doi.org/10.3997/2214-4609.202035095
- Evaluation of Regions of Influence for Dimensionality Reduction in Emulation of Production DataFerreira, C., Avansi, G., Vernon, I., Schiozer, D., & Goldstein, M. (2018, September). Evaluation of Regions of Influence for Dimensionality Reduction in Emulation of Production Data. Presented at ECMOR XVI - 16th European Conference on the Mathematics of Oil Recovery, Barcenola, Spain. https://doi.org/10.3997/2214-4609.201802145
- Matching hydrocarbon reservoir history - a Bayes linear approachCraig, P., Smith, J., Goldstein, M., & Seheult, A. (1995). Matching hydrocarbon reservoir history - a Bayes linear approach. Presented at Third International Applied Statistics in Industry Conference.
Journal Article
- Systematic structural discrepancy assessment for computer modelsGoldstein, M., Vernon, I., & Cumming, J. A. (2025). Systematic structural discrepancy assessment for computer models. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 383(2293), Article 20240214. https://doi.org/10.1098/rsta.2024.0214
- Calibration under Uncertainty Using Bayesian Emulation and History Matching: Methods and Illustration on a Building Energy ModelDomingo, D., Royapoor, M., Du, H., Boranian, A., Walker, S., & Goldstein, M. (2024). Calibration under Uncertainty Using Bayesian Emulation and History Matching: Methods and Illustration on a Building Energy Model. Energies, 17(16), Article 4014. https://doi.org/10.3390/en17164014
- Emulation and History Matching using the hmer PackageIskauskas, A., Vernon, I., Goldstein, M., Scarponi, D., McKinley, T. J., White, R. G., & McCreesh, N. (2024). Emulation and History Matching using the hmer Package. Journal of Statistical Software, 109(10), 1–48. https://doi.org/10.18637/jss.v109.i10
- Demonstrating multi-country calibration of a tuberculosis model using new history matching and emulation package - hmerScarponi, D., Iskauskas, A., Clark, R. A., Vernon, I., McKinley, T. J., Goldstein, M., Mukandavire, C., Deol, A., Weerasuriya, C., Bakker, R., White, R. G., & McCreesh, N. (2023). Demonstrating multi-country calibration of a tuberculosis model using new history matching and emulation package - hmer. Epidemics, 43, Article 100678. https://doi.org/10.1016/j.epidem.2023.100678
- Complex model calibration through emulation, a worked example for a stochastic epidemic modelDunne, M., Mohammadi, H., Challenor, P., Borgo, R., Porphyre, T., Vernon, I., Firat, E. E., Turkay, C., Torsney-Weir, T., Goldstein, M., Reeve, R., Fang, H., & Swallow, B. (2022). Complex model calibration through emulation, a worked example for a stochastic epidemic model. Epidemics, 39, Article 100574. https://doi.org/10.1016/j.epidem.2022.100574
- Challenges in estimation, uncertainty quantification and elicitation for pandemic modellingSwallow, B., Birrell, P., Blake, J., Burgman, M., Challenor, P., Coffeng, L. E., Dawid, P., De Angelis, D., Goldstein, M., Hemming, V., Marion, G., McKinley, T. J., Overton, C. E., Panovska-Griffiths, J., Pellis, L., Probert, W., Shea, K., Villela, D., & Vernon, I. (2022). Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling. Epidemics, 38. https://doi.org/10.1016/j.epidem.2022.100547
- Varying Coefficient Models and Design Choice for Bayes Linear Emulation of Complex Computer Models with Limited Model EvaluationsWilson, A. L., Goldstein, M., & Dent, C. J. (2022). Varying Coefficient Models and Design Choice for Bayes Linear Emulation of Complex Computer Models with Limited Model Evaluations. SIAM/ASA/Journal/on/Uncertainty/Quantification, 10(1), 350-378. https://doi.org/10.1137/20m1318560
- Intermediate Variable Emulation: using internal processes in simulators to build more informative emulatorsOughton, R., Goldstein, M., & Hemmings, J. (2022). Intermediate Variable Emulation: using internal processes in simulators to build more informative emulators. SIAM/ASA/Journal/on/Uncertainty/Quantification, 10(1), 268-293. https://doi.org/10.1137/20m1370902
- Bayes linear analysis for ordinary differential equationsJones, M., Goldstein, M., Randell, D., & Jonathan, P. (2021). Bayes linear analysis for ordinary differential equations. Computational Statistics & Data Analysis, 161, Article 107228. https://doi.org/10.1016/j.csda.2021.107228
- Optimization via Statistical Emulation and Uncertainty Quantification: Hosting Capacity Analysis of Distribution NetworksDu, H., Sun, W., Goldstein, M., & Harrison, G. (2021). Optimization via Statistical Emulation and Uncertainty Quantification: Hosting Capacity Analysis of Distribution Networks. IEEE Access, 9, 118472-118483. https://doi.org/10.1109/access.2021.3105935
- Efficient Selection of Reservoir Model Outputs within an Emulation-Based Bayesian History Matching Uncertainty AnalysisFerreira, C., Vernon, I., Caiado, C., Formentin, H., Avansi, G., Goldstein, M., & Schiozer, D. (2020). Efficient Selection of Reservoir Model Outputs within an Emulation-Based Bayesian History Matching Uncertainty Analysis. SPE Journal, 25(4), 2119-2142. https://doi.org/10.4043/29801-ms
- Gaining more understanding about reservoir behavior through assimilation of breakthrough time and productivity deviation in the history matching processFormentin, H. N., Almeida, F. la R., Avansi, G. D., Maschio, C., Schiozer, D. J., Caiado, C., Vernon, I., & Goldstein, M. (2019). Gaining more understanding about reservoir behavior through assimilation of breakthrough time and productivity deviation in the history matching process. Journal of Petroleum Science and Engineering, 173, 1080-1096. https://doi.org/10.1016/j.petrol.2018.10.045
- Bayes linear analysis of risks in sequential optimal design problemsJones, M., Goldstein, M., Jonathan, P., & Randell, D. (2018). Bayes linear analysis of risks in sequential optimal design problems. Electronic Journal of Statistics, 12(2), 4002-4031. https://doi.org/10.1214/18-ejs1496
- Emulation of reservoir production forecast considering variation in petrophysical propertiesMoreno, R., Avansi, G., Schiozer, D., Vernon, I., Goldstein, M., & Caiado, C. (2018). Emulation of reservoir production forecast considering variation in petrophysical properties. Journal of Petroleum Science and Engineering, 165, 711-725. https://doi.org/10.1016/j.petrol.2018.02.056
- Quantifying uncertainty in wholesale electricity price projections using Bayesian emulation of a generation investment modelWilson, A., Dent, C., & Goldstein, M. (2018). Quantifying uncertainty in wholesale electricity price projections using Bayesian emulation of a generation investment model. Sustainable Energy, Grids and Networks, 13, 42-55. https://doi.org/10.1016/j.segan.2017.11.003
- History matching of a complex epidemiological model of human immunodeficiency virus transmission by using variance emulationAndrianakis, I., Vernon, I., McCreesh, N., McKinley, T., Oakley, J., Nsubuga, R., Goldstein, M., & White, R. (2017). History matching of a complex epidemiological model of human immunodeficiency virus transmission by using variance emulation. Journal of the Royal Statistical Society: Series C, 66(4), 717-740. https://doi.org/10.1111/rssc.12198
- Bayesian uncertainty analysis for complex physical systems modelled by computer simulators with applications to tipping pointsCaiado, C., & Goldstein, M. (2015). Bayesian uncertainty analysis for complex physical systems modelled by computer simulators with applications to tipping points. Communications in Nonlinear Science and Numerical Simulation, 26(1-3), 123-136. https://doi.org/10.1016/j.cnsns.2015.02.006
- Posterior Belief Assessment: Extracting Meaningful Subjective Judgements from Bayesian Analyses with Complex Statistical ModelsWilliamson, D., & Goldstein, M. (2015). Posterior Belief Assessment: Extracting Meaningful Subjective Judgements from Bayesian Analyses with Complex Statistical Models. Bayesian Analysis, 10(4). https://doi.org/10.1214/15-ba966si
- "Second-order exchangeability analysis for multi-model ensemblesRougier, J., Goldstein, M., & House, L. (2013). "Second-order exchangeability analysis for multi-model ensembles. Journal of the American Statistical Association, 108(503), 852-863. https://doi.org/10.1080/01621459.2013.802963
- Fast Linked Analyses for Scenario-based HierarchiesWilliamson, D., Goldstein, M., & Blaker, A. (2012). Fast Linked Analyses for Scenario-based Hierarchies. Journal of the Royal Statistical Society: Series C, 61(5), 665-691. https://doi.org/10.1111/j.1467-9876.2012.01042.x
- Bayesian Strategies to Assess Uncertainty in Velocity ModelsCaiado, C. C., Goldstein, M., & Hobbs, R. W. (2012). Bayesian Strategies to Assess Uncertainty in Velocity Models. Bayesian Analysis, 7(1), 211-234. https://doi.org/10.1214/12-ba707
- Bayesian Policy Support for Adaptive Strategies using Computer Models for Complex Physical SystemsWilliamson, D., & Goldstein, M. (2012). Bayesian Policy Support for Adaptive Strategies using Computer Models for Complex Physical Systems. Journal of the Operational Research Society, 63(8), 1021-1033. https://doi.org/10.1057/jors.2011.110
- Galaxy Formation: a Bayesian Uncertainty AnalysisVernon, I., Goldstein, M., & Bower, R. G. (2010). Galaxy Formation: a Bayesian Uncertainty Analysis. Bayesian Analysis, 05(04), 619-670. https://doi.org/10.1214/10-ba524
- Sensitivity of decisions with imprecise utility trade-off
parameters using boundary linear utilityFarrow, M., & Goldstein, M. (2010). Sensitivity of decisions with imprecise utility trade-offparameters using boundary linear utility. International Journal of Approximate Reasoning, 51. https://doi.org/10.1016/j.ijar.2010.08.002
- Bayesian linear inspection planning for large-scale physical systemsRandell, 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. https://doi.org/10.1243/1748006xjrr322
- Small Sample Bayesian Designs for Complex High-Dimensional Models Based on Information Gained Using Fast ApproximationsCumming, 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. https://doi.org/10.1198/tech.2009.08015
- Reified Bayesian modelling and inference for physical systemsGoldstein, M., & Rougier, J. (2009). Reified Bayesian modelling and inference for physical systems. Journal of Statistical Planning and Inference, 139(3), 1221-1239. https://doi.org/10.1016/j.jspi.2008.07.019
- Almost-Pareto decision sets in imprecise utility hierarchiesFarrow, M., & Goldstein, M. (2009). Almost-Pareto decision sets in imprecise utility hierarchies. Journal of Statistical Theory and Practice, 3, 137-155.
- Prior viability assessment for Bayesian analysis, Journal of
Statistical Planning and InferenceGoldstein, M., & Seheult, A. (2008). Prior viability assessment for Bayesian analysis, Journal ofStatistical Planning and Inference. Journal of Statistical Planning and Inference, 138, 1271-1286.
- Bayes Linear Calibrated Prediction for Complex SystemsGoldstein, M., & Rougier, J. (2006). Bayes Linear Calibrated Prediction for Complex Systems. Journal of the American Statistical Association, 101(475), 1132-1143. https://doi.org/10.1198/016214506000000203
- Trade-off sensitive experimental design: a multicriterion, decision theoretic, Bayes linear approachFarrow, 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. https://doi.org/10.1016/j.jspi.2004.07.008
- Subjective Bayesian analysis: principles and practice.Goldstein, M. (2006). Subjective Bayesian analysis: principles and practice. Bayesian Analysis, 1, 403-420. https://doi.org/10.1214/06-ba116
- Probabilistic formulations for transferring inferences from
mathematical models to physical systems.Goldstein, M., & Rougier, J. (2005). Probabilistic formulations for transferring inferences frommathematical models to physical systems. SIAM Journal on Scientific Computing. SIAM Journal on Scientific Computing., 26, 467-487.
- Bayes linear kinematics and Bayes linear Bayes Graphical ModelsGoldstein, M., & Shaw, S. (2004). Bayes linear kinematics and Bayes linear Bayes Graphical Models. Biometrika, 91(2), 425-446. https://doi.org/10.1093/biomet/91.2.425
- Moral dominance relations for program comprehensionShaw, S., Goldstein, M., Munro, M., & Burd, E. (2003). Moral dominance relations for program comprehension. IEEE Transactions on Software Engineering, 29(9), 851-863. https://doi.org/10.1109/tse.2003.1232289
- Bayesian Graphical Models for Software TestingWooff, D., Goldstein, M., & Coolen, F. (2002). Bayesian Graphical Models for Software Testing. IEEE Transactions on Software Engineering, 28(5), 510-525. https://doi.org/10.1109/tse.2002.1000453
- Generalized partition testing via Bayes linear methodsCoolen, F., Goldstein, M., & Munro, M. (2001). Generalized partition testing via Bayes linear methods. Information and Software Technology, 43(13), 783-793. https://doi.org/10.1016/s0950-5849%2801%2900185-9
- Bayesian forecasting for complex systems using computer simulatorsCraig, P., Goldstein, M., Rougier, J., & Seheult, A. (2001). Bayesian forecasting for complex systems using computer simulators. Journal of the American Statistical Association, 96(454), 717-729. https://doi.org/10.1198/016214501753168370
- Avoiding foregone conclusions: geometric and foundational analysis of paradoxes of finite additivityGoldstein, M. (2001). Avoiding foregone conclusions: geometric and foundational analysis of paradoxes of finite additivity. Journal of Statistical Planning and Inference, 94(1), 73-87. https://doi.org/10.1016/s0378-3758%2800%2900229-9
- A Bayesian Analysis of Fluid Flow in PipelinesRougier, J., & Goldstein, M. (2001). A Bayesian Analysis of Fluid Flow in Pipelines. Journal of the Royal Statistical Society: Series C, 50(1), 77-93. https://doi.org/10.1111/1467-9876.00221
- Managing the uncertainties of software testing: a Bayesian approach.Rees, K., Coolen, F., Goldstein, M., & Wooff, D. (2001). Managing the uncertainties of software testing: a Bayesian approach. Quality and Reliability Engineering International, 17, 191-203.
- Restricted prior inference for complex uncertainty structuresGoldstein, M., & Wilkinson, D. (2001). Restricted prior inference for complex uncertainty structures. Annals of Mathematics and Artificial Intelligence, 32, 315-334. https://doi.org/10.1023/a%3A1016782020717
- Bayes Linear Methods III - Analysing Bayes linear influence diagrams and Exchangeability in [B/D].Wooff, D., & Goldstein, M. (2000). Bayes Linear Methods III - Analysing Bayes linear influence diagrams and Exchangeability in [B/D]. JOURNAL OF STATISTICAL SOFTWARE, 5(2).
- Bayes linear analysis for graphical models: the geometric approach to local computation and interpretive graphicsGoldstein, M., & Wilkinson, D. (2000). Bayes linear analysis for graphical models: the geometric approach to local computation and interpretive graphics. Statistics and Computing, 10, 311-324.
- Constructing partial prior specifications for models of complex physical systems.Craig, P., Goldstein, M., Seheult, A., & Smith, J. (1998). Constructing partial prior specifications for models of complex physical systems. Journal of the Royal Statistical Society: Series D, 47(1), 37-53. https://doi.org/10.1111/1467-9884.00115
- Adjusting exchangeable beliefs.Goldstein, M., & Wooff, D. (1998). Adjusting exchangeable beliefs. Biometrika, 85, 39-54. https://doi.org/10.1093/biomet/85.1.39
- Choosing samples sizes in balanced experimental designs: a Bayes linear approach.Goldstein, M., & Wooff, D. (1997). Choosing samples sizes in balanced experimental designs: a Bayes linear approach. Journal of the Royal Statistical Society: Series D, 46, 167-183.
- Bayes linear sufficiency and systems of expert posterior assessmentsGoldstein, M., & O’Hagan, A. (1996). Bayes linear sufficiency and systems of expert posterior assessments. Journal of the Royal Statistical Society: Series B, 58, 301-316.
- Bayes linear computation: concepts, implementation and programming environment.Goldstein, M., & Wooff, D. (1995). Bayes linear computation: concepts, implementation and programming environment. Statistics and Computing, 5, 327-341.
- Robustness measures for Bayes linear analysis (with discussion).Goldstein, M., & Wooff, D. (1994). Robustness measures for Bayes linear analysis (with discussion). Journal of Statistical Planning and Inference, 40, 261-277.
Other (Digital/Visual Media)
- Beliefs adjusted by Data: the Bayes linear programming language, including software manuals and tutorials.Wooff, D., & Goldstein, M. (1995). Beliefs adjusted by Data: the Bayes linear programming language, including software manuals and tutorials.