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Level: MSci, MSc
Title: Kriging
Supervisor:

Dr Hugo Maruri-Aguilar
Research Area: Probability and Applications [Including Statistics]
Description:

Kriging is a tool for data modelling which is based around a structure of spatial dependence. It is a flexible and useful tool that can be used in a variety of scenarios ranging from regression-type scenarios and geospatial data to the analysis of computer experiments.

The project would consist of a revision of literature including computer experiments and variograms as well as analyses of data sets. Initial data analysis will use a simple example from computer experiments, while in a more advanced stage and depending on the student progress, analysis of a geospatial dataset will be tackled.
Further Reading:
  • M. Bachmaier, M. Backes, Variogram or semivariogram? Variance or semivariance? Allan variance or introducing a new term?, Math. Geosci. 43 (2011) 735–740.
  • N. Cressie, The origins of kriging, Math. Geol. 22 (1990) 239–252.
  • J. Sacks, W. J. Welch, T. J. Mitchell, H. P. Wynn, Design and analysis of computer experiments, Stat. Sci. 4 (1989) 409–435.
Key Modules:

MTH6116 Design of Experiments (desirable)

MTH6134 Statistical Modelling II (desirable)
Other Information:

Some programming experience is desirable. Languages/packages involved: GEM-SA, R, Maple. Report to be written in LaTeX.
Current Availability: Yes