Supporting materials

Data Quality Assessment
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Model Analysis and Uncertainty Quantification
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Psychological Experiments
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Related datasets, collections and other links

Recommended reading

  • Gramacy RB (2020) Surrogates. Gaussian process modeling, design and optimization for the applied sciences. Boca Raton, FL: CRC/Chapman and Hall. Ebook:
  • Fang K-T, R Li, A Sudjianto (2006) Design and Modeling for Computer Experiments. Boca Raton, FL: CRC/Chapman and Hall.
  • Santner TJ, BJ Williams, WI Notz (2003) The Design and Analysis of Computer Experiments. New York: Springer.
  • Articles and other materials:
  • Hilton J (2017) Managing uncertainty in agent-based demographic models. University of Southampton, Doctoral Thesis, 119pp.
  • Kennedy M, O’Hagan A (2001) Bayesian calibration of computer models. Journal of the Royal Statistical Society B, 63(3), 425–464.
  • Kleijnen JPC (1995) Verification and validation of simulation models. European Journal of Operational Research, 82(1): 145–162.
  • MUCM (Managing Uncertainty in Complex Models): website with online resources, methods toolkit and extensive documentation. See:; and the toolkit:
  • Nurse S and Bijak J (2019) Data and Knowledge for Modelling Asylum Migration. Meta-information on data sources on Syrian migration into Europe. Mimeos, University of Southampton.
  • O’Hagan, A. (2006). Bayesian analysis of computer code outputs: A tutorial. Reliability Engineering & System Safety, 91(10–11), 1290–1300.
  • Silverman E, Hilton J, Noble J and Bijak J (2013) Simulating the cost of social care in an ageing population. In: W Rekdalsbakken, RT Bye and
  • H Zhang (eds.) Proceedings of the 27th ECMS, p. 689–695.