Staff profile

• Applied statistics
• Bayesian Statistics
• Modelling uncertainty in complex systems
• Maths education in the early years

• Statistics

Conference Paper

• Oughton, R.H., Wooff, D.A., Swarbrick, R.E. & Hobbs, R.W. (2015), Modelling Uncertainty in Pore Pressure Using Dynamic Bayesian Networks, 77th EAGE Conference & Exhibition 2015: Earth Science for Energy and Environment. Madrid, Spain, European Association of Geoscientists and Engineers (EAGE), Th N114 01.

Journal Article

• Oughton, Rachel, Nichols, Kathryn, Bolden, David S., Dixon-Jones, Sarah, Fearn, Sam, Darwin, Sophia, Mistry, Mrita, Peyerimhoff, Norbert & Townsend, Adam (2022). Developing ‘deep mathematical thinking’ in geometry with 3- and 4-year-olds: A collaborative study between early years teachers and University-based mathematicians. Mathematical Thinking and Learning
• Benson, Tony, Bucher, Tamara, Oughton, Rachel, McCloat, Amanda, Mooney, Elaine, Farrell, Sarah & Dean, Moira (2022). The effects of nutrition and health claims on the nutrient composition of single and subsequent meal servings. Appetite 176: 106105.
• Oughton, Rachel, Goldstein, Michael & Hemmings, John (2022). Intermediate Variable Emulation: using internal processes in simulators to build more informative emulators. SIAM/ASA Journal on Uncertainty Quantification 10(1): 268-293.
• Oughton, Rachel H., Wooff, David A., Hobbs, Richard W., Swarbrick, Richard E. & O'Connor, Stephen A. (2018). A sequential dynamic Bayesian network for pore pressure estimation with uncertainty quantification. Geophysics 83(2): D27-D39.
• Mathias, S.A., McIntyre, N. & Oughton, R.H. (2016). A study of non-linearity in rainfall-runoff response using 120 UK catchments. Journal of Hydrology 540: 423-436.
• Oughton, Rachel H. & Craig, Peter S. (2016). Hierarchical Emulation: a method for modeling and comparing nested simulators. SIAM/ASA Journal on Uncertainty Quantification 4(1): 495-519.
• Oughton, Rachel H., Wooff, David A. & O'Connor, Stephen A. (2014). A Bayesian shifting method for uncertainty in the open-hole gamma-ray log around casing points. Petroleum Geoscience 20(4): 375-391.

Report

• Oughton, R.H., Wooff, D.A., Hobbs, R.W., O'Connor, S.A. & Swarbrick, R.E. (2015). Quantifying uncertainty in pore pressure estimation using Bayesian networks, with application to use of an offset well. Petroleum Geostatistics 2015. Biarritz, France, European Association of Geoscientists and Engineers (EAGE).