Temporal evolution of the extreme excursions of multivariate $k$th order Markov processes with application to oceanographic data
Methodology
2023-03-01 v1 Atmospheric and Oceanic Physics
Applications
Abstract
We develop two models for the temporal evolution of extreme events of multivariate th order Markov processes. The foundation of our methodology lies in the conditional extremes model of Heffernan & Tawn (2004), and it naturally extends the work of Winter & Tawn (2016,2017) and Tendijck et al. (2019) to include multivariate random variables. We use cross-validation-type techniques to develop a model order selection procedure, and we test our models on two-dimensional meteorological-oceanographic data with directional covariates for a location in the northern North Sea. We conclude that the newly-developed models perform better than the widely used historical matching methodology for these data.
Keywords
Cite
@article{arxiv.2302.14501,
title = {Temporal evolution of the extreme excursions of multivariate $k$th order Markov processes with application to oceanographic data},
author = {Stan Tendijck and Philip Jonathan and David Randell and Jonathan Tawn},
journal= {arXiv preprint arXiv:2302.14501},
year = {2023}
}