On the public citation graph
Distributions of return values for ocean wave characteristics in the South China Sea using directional–seasonal extreme value analysis
0 signed · 63 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1016/j.csda.2015.09.006openalex-snapshot
Fast computation of large scale marginal extremes with multi-dimensional covariates
inferredcites →https://doi.org/10.1016/j.oceaneng.2007.07.012openalex-snapshot
Seasonality and duration in extreme value distributions of significant wave height
inferredcites →https://doi.org/10.1016/j.oceaneng.2008.04.002openalex-snapshot
Statistical estimation of extreme ocean environments: The requirement for modelling directionality and other covariate effects
inferredcites →https://doi.org/10.1016/j.oceaneng.2010.01.017openalex-snapshot
On the use of discrete seasonal and directional models for the estimation of extreme wave conditions
inferredcites →https://doi.org/10.1016/j.oceaneng.2013.01.004openalex-snapshot
Statistical modelling of extreme ocean environments for marine design: A review
inferredcites →https://doi.org/10.1029/jc083ic05p02353openalex-snapshot
On the statistical distribution of wave heights in a storm
inferredcites →https://doi.org/10.1080/01621459.1987.10478410openalex-snapshot
Better Bootstrap Confidence Intervals
inferredcites →https://doi.org/10.1093/biomet/73.2.323openalex-snapshot
Approximate Predictive Likelihood
inferredcites →https://doi.org/10.1093/biomet/86.4.871openalex-snapshot
On prediction intervals based on predictive likelihood or bootstrap methods
inferredcites →https://doi.org/10.1093/biomet/asm015openalex-snapshot
Inference for clustered data using the independence loglikelihood
inferredcites →https://doi.org/10.1111/j.1467-9868.2004.02050.xopenalex-snapshot
A Conditional Approach for Multivariate Extreme Values (with Discussion)
inferredcites →https://doi.org/10.1111/j.1467-9868.2006.00543.xopenalex-snapshot
Generalized Linear Array Models with Applications to Multidimensional Smoothing
inferredcites →https://doi.org/10.1111/j.1467-9876.2005.00479.xopenalex-snapshot
Generalized Additive Modelling of Sample Extremes
inferredcites →https://doi.org/10.1115/1.2960859openalex-snapshot
The Effect of Directionality on Northern North Sea Extreme Wave Design Criteria
inferredcites →https://doi.org/10.1115/1.4029639openalex-snapshot
Estimation of Storm Peak and Intrastorm Directional–Seasonal Design Conditions in the North Sea
inferredcites →https://doi.org/10.1214/11-sts376openalex-snapshot
Statistical Modeling of Spatial Extremes
inferredcites →https://doi.org/10.3150/bj/1116340296openalex-snapshot
Nonparametric bootstrap prediction
inferredcites →https://doi.org/10.57805/revstat.v10i1.110openalex-snapshot
Review of Extreme Value Threshold Estimation and Uncertainty Quantification
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4822267openalex-extracted
Estimating Metocean Environments Associated with Extreme Structural Response
inferred← citeshttps://doi.org/10.1002/env.2403openalex-snapshot
Bayesian inference for nonstationary marginal extremes
inferred← citeshttps://doi.org/10.1002/env.2624openalex-snapshot
Flexible covariate representations for extremes
inferred← citeshttps://doi.org/10.1002/env.2655openalex-snapshot
A smoothing spline model for multimodal and skewed circular responses: Applications in meteorology and oceanography
inferred← citeshttps://doi.org/10.1002/env.2834openalex-snapshot
Temporal evolution of the extreme excursions of multivariate k$$ k $$th order Markov processes with application to oceanographic data
inferred← citeshttps://doi.org/10.1007/s40868-018-0046-6openalex-snapshot
A simple approach to account for seasonality in the description of extreme ocean environments
inferred← citeshttps://doi.org/10.1016/j.apor.2020.102165openalex-snapshot
Assessment of extreme waves in the North Atlantic Ocean by regional frequency analysis
inferred← citeshttps://doi.org/10.1016/j.apor.2020.102266openalex-snapshot
Bivariate regional extreme value analysis for significant wave height and wave period
inferred← citeshttps://doi.org/10.1016/j.coastaleng.2017.06.002openalex-snapshot
Regional frequency analysis of extreme waves in a coastal area
inferred← citeshttps://doi.org/10.1016/j.marstruc.2019.102680openalex-snapshot
Comparing different contour methods with response-based methods for extreme ship response analysis
inferred← citeshttps://doi.org/10.1016/j.marstruc.2020.102863openalex-snapshot
Marginal and total exceedance probabilities of environmental contours
inferred← citeshttps://doi.org/10.1016/j.marstruc.2023.103494openalex-snapshot
Global extreme wave estimates and their sensitivity to the analysed data period and data sources
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2016.04.010openalex-snapshot
Statistics of extreme ocean environments: Non-stationary inference for directionality and other covariate effects
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2017.06.059openalex-snapshot
Efficient estimation of return value distributions from non-stationary marginal extreme value models using Bayesian inference
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2018.10.027openalex-snapshot
Design conditions for waves and water levels using extreme value analysis with covariates
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2019.106347openalex-snapshot
Assessment of the uncertainty of estimated extreme quantiles by regional frequency analysis
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2019.106665openalex-snapshot
Directional–seasonal extreme value analysis of North Sea storm conditions
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2020.107406openalex-snapshot
Assessment of return value estimates from stationary and non-stationary extreme value models
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2020.107725openalex-snapshot
Uncertainties in return values from extreme value analysis of peaks over threshold using the generalised Pareto distribution
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2021.109642openalex-snapshot
Efficient estimation of distributional properties of extreme seas from a hierarchical description applied to calculation of un-manning and other weather-related operational windows
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2021.110407openalex-snapshot
Global extreme significant wave height within the dominant directional sector
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2022.113265openalex-snapshot
A penalised piecewise-linear model for non-stationary extreme value analysis of peaks over threshold
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2023.113959openalex-snapshot
Model-free environmental contours in higher dimensions
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2024.118754openalex-snapshot
Estimating metocean environments associated with extreme structural response to demonstrate the dangers of environmental contour methods
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2024.119247openalex-snapshot
Practical non-stationary extreme value analysis of peaks over threshold using the generalised Pareto distribution: Estimating uncertainties in return values
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2025.120502openalex-snapshot
An innovative deep learning model for accurate wave height predictions with enhanced performance for extreme waves
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2025.120672openalex-snapshot
Non-stationary extreme value models to account for the intensification of extreme typhoon waves
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2026.125510openalex-snapshot
Multivariate copula-based modelling of tropical cyclone-generated wind, wave, and current extremes: Comparative assessment for offshore sites in China
inferred← citeshttps://doi.org/10.1016/j.renene.2025.122489openalex-snapshot
Regional assessment of extreme tropical cyclone waves for marine renewable energy development
inferred← citeshttps://doi.org/10.1016/j.spasta.2018.04.007openalex-snapshot
Modelling spatial extreme events with environmental applications
inferred← citeshttps://doi.org/10.1080/01621459.2021.1996379openalex-snapshot
Modeling the Extremes of Bivariate Mixture Distributions With Application to Oceanographic Data
inferred← citeshttps://doi.org/10.1088/1755-1315/116/1/012066openalex-snapshot
Seasonal and Non-Seasonal Generalized Pareto Distribution to Estimate Extreme Significant Wave Height in The Banda Sea
inferred← citeshttps://doi.org/10.1109/hipcw.2016.017openalex-snapshot
Multi-dimensional Predictive Analytics for Risk Estimation of Extreme Events
inferred← citeshttps://doi.org/10.1115/1.4056786openalex-snapshot
Analyzing Extreme Sea State Conditions by Time-Series Simulation Accounting for Seasonality
inferred← citeshttps://doi.org/10.1115/1.4065968openalex-snapshot
The SPAR Model: A New Paradigm for Multivariate Extremes: Application to Joint Distributions of Metocean Variables
inferred← citeshttps://doi.org/10.1115/omae2019-95913openalex-snapshot
Spatial and Seasonal Variability of Metocean Design Criteria in the Southern South China Sea From Covariate Extreme Value Analysis
inferred← citeshttps://doi.org/10.1115/omae2022-78795openalex-snapshot
Analyzing Extreme Sea State Conditions by Time-Series Simulation
inferred← citeshttps://doi.org/10.1115/omae2024-130932openalex-snapshot
The SPAR Model: A New Paradigm for Multivariate Extremes. Application to Joint Distributions of Metocean Variables
inferred← citeshttps://doi.org/10.1680/jmaen.2019.20openalex-snapshot
Statistical description and modelling of extreme ocean wave conditions
inferred← citeshttps://doi.org/10.17635/lancaster/thesis/919openalex-snapshot
Conditional models for spatial extremes
inferred← citeshttps://doi.org/10.3390/app10144794openalex-snapshot
Correlation of Concurrent Extreme Metocean Hazards Considering Seasonality
inferred← citeshttps://doi.org/10.4043/26668-msopenalex-snapshot
Consistent Design Criteria for South China Sea With a Large-Scale Extreme Value Model
inferred← citeshttps://doi.org/10.5821/dissertation-2117-348910openalex-snapshot
Probabilistic characterization of single and concurrent metocean variables of Mexican coasts with seasonal variability using extreme value theory, with application to reliability of coastal structures
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.