Staff profile

• Statistics
• Applied Statistics
• Uncertainty Analysis
• Statistical Computation
• Variable Selection

• Statistics

Chapter in book

• Errington, Adam, Einbeck, Jochen & Cumming, Jonathan (2021). Estimating Exposure Fraction from Radiation Biomarkers: A Comparison of Frequentist and Bayesian Approaches. In Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications. Vasile, Massimiliano & Quagliarella, Domenico Cham: Springer. 8: 393-405.
• Hasan, Muhammad Mahmudul & Cumming, Jonathan A. (2021). Bayes Linear Emulation of Simulated Crop Yield. In Applied Statistics and Data Science: Proceedings of Statistics 2021 Canada, Selected Contributions. Chaubey, Yogendra P., Lahmiri, Salim, Nebebe, Fassil & Sen, Arusharka Cham: Springer. 375: 145-151.
• Cumming, J. A. & Goldstein, M. (2010). Bayes linear Uncertainty Analysis for Oil Reservoirs Based on Multiscale Computer Experiments. In The Oxford Handbook of Applied Bayesian Analysis. O'Hagan, A. & West, M. Oxford: Oxford University Press. 241-270.

Conference Paper

• Cumming, J A, Botsas, T, Jermyn, I H & Gringarten, A C (2020), Assessing the Non-Uniqueness of a Well Test Interpretation Model Using a Bayesian Approach, SPE Virtual Europec 2020. Society of Petroleum Engineers, SPE-200617-MS.
• Aluko, Lekan, Cumming, Jonathan & Gringarten, Alain (2020), Using Deconvolution to Estimate Unknown Well Production from Scarce Wellhead Pressure Data, SPE Annual Technical Conference and Exhibition. Virtual.
• Cumming, J A, Jaffrezic, V, Whittle, T & Gringarten, A C (2019), Constrained Least-Squares Multiwell Deconvolution, SPE Western Regional Meeting. San Jose, California, USA, Society of Petroleum Engineers.
• Jaffrezic, V., Razminia, K., Cumming, J. A. & Gringarten, A. C. (2019), Field Applications of Constrained Multiwell Deconvolution, SPE Europec featured at 81st EAGE Conference and Exhibition. London, UK.
• Tung, Y, Virues, C, Cumming, J A & Gringarten, A C (2016), Multiwell Deconvolution for Shale Gas, SPE Europec featured at 78th EAGE Conference and Exhibition. Vienna, Austria, SPE.
• Thornton, E J, Mazloom, J, Gringarten, A C & Cumming, J A (2015), Application of Multiple Well Deconvolution Method in a North Sea Field, EUROPEC 2015. Madrid, Spain, Society of Petroleum Engineers, Madrid.
• Cumming, J A, Wooff, D A, Whittle, T, Crossman, R J & Gringarten, A C (2013), Assessing the Non-Uniqueness of the Well Test Interpretation Model Using Deconvolution, 75th EAGE Annual Conference & Exhibition, 10–13 June 2013. London, United Kingdom, Society of Petroleum Engineers, London, 1-24.
• Cumming, J A, Wooff, D A, Whittle, T & Gringarten, A C (2013), Multiple Well Deconvolution, 2013 SPE Annual Technical Conference & Exhibition. New Orleans, USA, Society of Petroleum Engineers, New Orleans LA.

Doctoral Thesis

• Cumming, J A (2006). Clinical Decision Support. Department of Mathematical Sciences. Durham University. PhD.

Journal Article

• Botsas, T., Cumming, J. A. & Jermyn, I. H. (2022). A Bayesian multi-region radial composite reservoir model for deconvolution in well test analysis. Journal of the Royal Statistical Society: Series C (Applied Statistics) 71(4): 951-968.
• Errington, Adam, Einbeck, Jochen, Cumming, Jonathan, Rössler, Ute & Endesfelder, David (2022). The effect of data aggregation on dispersion estimates in count data models. The International Journal of Biostatistics 18(1): 183-202.
• Goldie, Stuart J., Bush, Scott, Cumming, Jonathan A. & Coleman, Karl S. (2020). Statistical Approach to Raman Analysis of Graphene-Related Materials: Implications for Quality Control. ACS Applied Nano Materials 3(11): 11229-11239.
• Vernon, I. R., Jackson, S. E. & Cumming, J. A. (2019). Known Boundary Emulation of Complex Computer Models. SIAM/ASA Journal on Uncertainty Quantification 7(3): 838-876.
• Cumming, J.A. & Goldstein, M. (2018). Bayesian decision analysis for complex physical systems via embedded computer models. SIAM / ASA Journal on Uncertainty Quantification (JUQ)
• Cumming, J. A., Wooff, D. A., Whittle, T. & Gringarten, A. C. (2014). Multiwell Deconvolution. SPE Reservoir Evaluation and Engineering 17(04): 457-465.
• Cumming, J. A. & Goldstein, M. (2009). Small Sample Bayesian Designs for Complex High-Dimensional Models Based on Information Gained Using Fast Approximations. Technometrics 51(4): 377-388.
• Cumming, J. A. & Wooff, D. A. (2007). Dimension reduction via principal variables. Computational Statistics & Data Analysis 52(1): 550-565.

Presentation

• Hasan, Muhammad M & Cumming, J A (2020), A Bayesian non-linear hierarchical framework for crop models based on big data outputs, 13th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2020). King's College London, England.

Report

• Cumming, J. A., Riseth, A. & Williams, J. (2016). Understanding the accuracy of pre-symptomatic diagnosis of sepsis. Department of Mathematical Sciences. Durham, European Study Group in Industry 116 (ESGI 116).

Working Paper

• Cumming, J. A. & Wooff, D. A. (2009). Standardized profile plots for multivariate repeated measures data.