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5 papers · 1 filter

stat.ME2025

Gaussian mixture copulas for flexible dependence modelling in the body and tails of joint distributions

Lídia M. André, Jonathan A. Tawn

Fully describing the entire data set is essential in multivariate risk assessment, since moderate levels of one variable can influence another, potentially leading it to be extreme…

stat.ME2024

Automated threshold selection and associated inference uncertainty for univariate extremes

Conor Murphy, Jonathan A. Tawn, Zak Varty

Threshold selection is a fundamental problem in any threshold-based extreme value analysis. While models are asymptotically motivated, selecting an appropriate threshold for finite…

stat.ME2024

Estimating the limiting shape of bivariate scaled sample clouds: with additional benefits of self-consistent inference for existing extremal dependence properties

Emma S. Simpson, Jonathan A. Tawn

The key to successful statistical analysis of bivariate extreme events lies in flexible modelling of the tail dependence relationship between the two variables. In the extreme valu…

stat.ME2024

Estimating Metocean Environments Associated with Extreme Structural Response to Demonstrate the Dangers of Environmental Contour Methods

Matthew Speers, David Randell, Jonathan Angus Tawn +1

Extreme value analysis (EVA) uses data to estimate long-term extreme environmental conditions for variables such as significant wave height and period, for the design of marine str…

stat.ME2024

Extremal properties of max-autoregressive moving average processes for modelling extreme river flows

Eleanor D'Arcy, Jonathan A Tawn

Max-autogressive moving average (Max-ARMA) processes are powerful tools for modelling time series data with heavy-tailed behaviour; these are a non-linear version of the popular au…