A5042139256- Climate variability and models
- Hydrology and Drought Analysis
- Financial Risk and Volatility Modeling
- Ocean Waves and Remote Sensing
- Probabilistic and Robust Engineering Design
- Structural Integrity and Reliability Analysis
- Oceanographic and Atmospheric Processes
- Wind and Air Flow Studies
- Tropical and Extratropical Cyclones Research
- Insurance and Financial Risk Management
- Structural Health Monitoring Techniques
- Ship Hydrodynamics and Maneuverability
- Optimization and Mathematical Programming
- Soil Geostatistics and Mapping
- Anomaly Detection Techniques and Applications
- Statistical Methods and Bayesian Inference
- Scheduling and Timetabling Solutions
- Risk and Portfolio Optimization
- Reservoir Engineering and Simulation Methods
- Insurance, Mortality, Demography, Risk Management
- Spatial and Panel Data Analysis
- Scheduling and Optimization Algorithms
- Forecasting Techniques and Applications
Shell (Netherlands)
2018-2024
Technology Centre Prague
2023
Shell (United Kingdom)
2016-2017
The covXtreme software provides functionality for estimation of marginal and conditional extreme value models, non-stationary with respect to covariates, environmental design contours. Generalised Pareto (GP) models peaks over threshold are estimated, using a piecewise-constant representation the variation GP scale parameters on (potentially multidimensional) covariate domain interest. one or more associated variates, given large single conditioning variate, is described extremes model...
We describe a model for the conditional dependence of spatial process measured at one or more remote locations given extreme values conditioning location, motivated by extremes methodology Heffernan and Tawn. Compared to alternative descriptions in terms max-stable processes, is advantageous because it conceptually straightforward admits different forms extremal (including asymptotic independence). use within Bayesian framework estimate ocean storm severity (quantified using significant wave...
The joint extremal spatial dependence of wind speed and significant wave height in the North East Atlantic is quantified using Metop satellite scatterometer hindcast observations for period 2007–2018, a multivariate conditional extremes (MSCE) model, ultimately motivated by work Heffernan Tawn (2004). analysis involves (a) registering individual swaths corresponding data onto template transect (running approximately north-east to south-west, between British Isles Iceland), (b) non-stationary...
Abstract Physical considerations and previous studies suggest that extremal dependence between ocean storm severity at two locations exhibits near asymptotic short inter-location distances, leading to independence perfect with increasing distance. We present a spatial conditional extremes (SCE) model for severity, characterising of severe storms by distance direction. The is an extension Shooter et al. 2019 (Environmetrics 30 , e2562, 2019) Wadsworth Tawn (2019), incorporating piecewise...
Abstract The extremal spatial dependence of significant wave height in the North East Atlantic is explored using Joint Altimetry Satellite Oceanography Network satellite altimeter observations for period 2002–2018, and a conditional extremes model motivated by work Heffernan Tawn. analysis involves (a) registering individual passes onto template transect, (b) marginal extreme value at set locations on transect transformation from physical to standard Laplace scale, (c) estimation (d)...
Abstract Motivated by recent work on Markov extremal models, we develop a nonstationary extension and use it to characterize the time evolution of extreme sea state significant wave height ( H S ) storm direction in vicinity peak state. The approach first requires transformation from physical standard Laplace scale achieved using directional marginal value model. Laplace‐scale is subsequently characterized model that rate change described an autoregressive model, variance which ‐dependent....
Abstract This paper describes spatial and seasonal variability of metocean design criteria in the southern South China Sea. Non-stationary extreme value analysis was performed using CEVA approach (Covariate Extreme Value Analysis,[1]) for a 59-year long SEAFINE hindcast winds waves, estimating up to 10,000-year return period. Wind are mostly driven by large-scale monsoonal events; at higher periods infrequent cyclonic events have strong influence on tail distribution but confined limited...
covXtreme is MATLAB software for estimation of marginal and conditional extreme value models, non-stationary with respect to covariates, environmental design contours. Generalised Pareto models peaks over threshold are estimated, using a piecewise-constant representation the variation scale parameters on covariate domain interest. The one or more associated variates, given large single conditioning variate, described extremes model Heffernan Tawn (2004). Optimal smoothness covariates...
Abstract Environmental contours are used in structural reliability analysis of marine and coastal structures as an approximate means to locate the boundary distribution environmental variables, identify conditions giving rise extreme loads responses. There different approaches estimating contours, some directly linked methods reliability. Each contouring approach has its pros cons. Although procedures for applying design have been reported articles standards, there is still ambiguity about...
Modelling rare or extreme events is critical in many domains, including financial risk, computer security breach, network outage, corrosion and fouling, manufacturing quality environmental extremes such as floods, snowfalls, heat-waves, seismic hazards meteorological-oceanographic like extra-tropical storms, hurricanes typhoons. Statistical modelling enables us to understand design mechanisms prevent their occurrence manage impact. Extreme are challenging characterise they are, by...
The covXtreme software provides functionality for estimation of marginal and conditional extreme value models, non-stationary with respect to covariates, environmental design contours. Generalised Pareto (GP) models peaks over threshold are estimated, using a piecewise-constant representation the variation GP scale parameters on (potentially multidimensional) covariate domain interest. one or more associated variates, given large single conditioning variate, is described extremes model...