A modeler's guide to extreme value software
This review paper surveys recent development in software implementations for extreme
value analyses since the publication of Stephenson and Gilleland (Extremes 8: 87–109,) …
value analyses since the publication of Stephenson and Gilleland (Extremes 8: 87–109,) …
[HTML][HTML] Estimation of associated values from conditional extreme value models
The design and reanalysis of offshore and coastal structures usually requires the estimation
of return values for dominant metocean variables (such as significant wave height) and …
of return values for dominant metocean variables (such as significant wave height) and …
Deep learning of multivariate extremes via a geometric representation
CJR Murphy-Barltrop, R Majumder… - arXiv preprint arXiv …, 2024 - arxiv.org
The study of geometric extremes, where extremal dependence properties are inferred from
the deterministic limiting shapes of scaled sample clouds, provides an exciting approach to …
the deterministic limiting shapes of scaled sample clouds, provides an exciting approach to …
A multivariate model to estimate environmental load on an offshore structure
Offshore structures such as oil platforms are subjected to significant environmental loads
caused by wind, waves, and current. The complexity of offshore environment requires robust …
caused by wind, waves, and current. The complexity of offshore environment requires robust …
Statistical modeling and dependence analysis for tide level via multivariate extreme value distribution method
A Tian, X Shu, J Guo, H Li, R Ye, P Ren - Ocean Engineering, 2023 - Elsevier
This paper presents a statistical modeling approach to explore the dependence of extreme
values in multi-site tidal water levels (TL) using hourly data from six tidal stations in the …
values in multi-site tidal water levels (TL) using hourly data from six tidal stations in the …
Temporal evolution of the extreme excursions of multivariate kk th order Markov processes with application to oceanographic data
We develop two models for the temporal evolution of extreme events of multivariate kk th
order Markov processes. The foundation of our methodology lies in the conditional extremes …
order Markov processes. The foundation of our methodology lies in the conditional extremes …
[HTML][HTML] covXtreme: MATLAB software for non-stationary penalised piecewise constant marginal and conditional extreme value models
The covXtreme software provides functionality for estimation of marginal and conditional
extreme value models, non-stationary with respect to covariates, and environmental design …
extreme value models, non-stationary with respect to covariates, and environmental design …
Fast spatial simulation of extreme high-resolution radar precipitation data using integrated nested Laplace approximations
Aiming to deliver improved precipitation simulations for hydrological impact assessment
studies, we develop a methodology for modelling and simulating high-dimensional spatial …
studies, we develop a methodology for modelling and simulating high-dimensional spatial …
Combining uncertain machine learning predictions and numerical simulation results for the extreme value analysis of cyclone-induced wave heights–Application in …
J Rohmer, AG Filippini, R Pedreros - Ocean Modelling, 2023 - Elsevier
Assessing return level RL (with return period typically ranging from 100 to 500 years) for
extreme waves in cyclone-prone regions is often made problematic by the lack of sufficient …
extreme waves in cyclone-prone regions is often made problematic by the lack of sufficient …
An efficient workflow for modelling high-dimensional spatial extremes
We develop a comprehensive methodological workflow for Bayesian modelling of high-
dimensional spatial extremes that lets us describe both weakening extremal dependence at …
dimensional spatial extremes that lets us describe both weakening extremal dependence at …