10 citations · 13 across the 7 of their papers we have counts for
6 papers · 1 filter
Modelling non-stationary extremal dependence through a geometric approach
C. J. R. Murphy-Barltrop, J. L. Wadsworth, M. de Carvalho +1
Non-stationary extremal dependence, whereby the relationship between the extremes of multiple variables evolves over time, is commonly observed in many environmental and financial…
Discrete Gaussian Vector Fields On Meshes
Michael Gillan, Stefan Siegert, Ben Youngman
Though the underlying fields associated with vector-valued environmental data are continuous, observations themselves are discrete. For example, climate models typically output gri…
Flexible models for nonstationary dependence: Methodology and examples
Benjamin D. Youngman
There are many situations when modelling environmental phenomena for which it is not appropriate to assume a stationary dependence structure. \cite{sampson1992} proposed an approac…
Inference for spatial processes using imperfect data from measurements and numerical simulations
Benjamin D. Youngman, David B. Stephenson
We present a framework for inference for spatial processes that have actual values imperfectly represented by data. Environmental processes represented as spatial fields, either at…
Calibration of Complex Computer Simulators using Likelihood Emulation
Jeremy E. Oakley, Benjamin D. Youngman
We calibrate a Natural History Model, which is a class of computer simulator used in the health industry, and here has been used to characterise bowel cancer incidence for the UK.…
Spatial Interpolation of Extreme Values
B. D. Youngman
This paper introduces a method for spatial interpolation of extreme values, and in particular targets the case in which conventional data, resulting from a measurement for example,…