Type: Seminar

Distribution: World

Expiry: 27 May 2016

CalTitle1: Symbolic data analysis for extremes

Auth: jormerod@pjormerod5.pc (assumed)

Abstract: Symbolic data analysis (SDA) is an underdeveloped statistical method in which the individual "data points" for analysis are themselves distributions. How to construct and then analyse these "symbols" is an ongoing research problem. This talk will briefly introduce the ideas behind SDA, before demonstrating how they can be used to fit extreme value distributions with an arbitrarily large numbers of classical observations. This procedure can be shown to offer one way to fit max-stable process models using pairwise (or higher) composite-likelihoods with an arbitrarily large number of spatial locations, which would otherwise be computationally prohibitive. (Note: This talk was recently presented at an extreme value theory workshop, hence the focus on extremes. The methods and ideas are broadly applicable however). *** Note the change of location to Carslaw 273 ***