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Thursday 31 Oct 2019Flexible models for nonstationary dependence: methodology and a risk analysis example

Dr Ben Youngman - University of Exeter

Harrison 101 14:30-16:30

When modelling a process we often assume that its dependence structure is stationary; e.g. doesn't change with location in a spatial model or doesn't change over input space in an emulator. But if we're dealing with a large spatial domain or input space, we must at some point think our dependence structure is nonstationary. Sampson & Guttorp (JASA, 1992), and various subsequent works, incorporated nonstationarity in the spatial context by transforming locations' geographic space to a new space in which stationarity was a fair (or at least better) assumption. This talk will discuss a new approach that aims to synthesise and make more intuitive some past works while also allowing objective inference. An example related to risk analysis, based on loss estimation for US rainfall, will be used for illustration.

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