The DOI matches its Crossref record.
Dependence modelling for spatial extremes
Abstract
Current dependence models for spatial extremes are based upon max-stable processes. Within this class, there are few inferentially viable models available, and we propose one further model. More problematic are the restrictive assumptions that must be made when using max-stable processes to model dependence for spatial extremes: it must be assumed that the dependence structure of the observed extremes is compatible with a limiting model that holds for all events more extreme than those that have already occurred. This problem has long been acknowledged in the context of finite-dimensional multivariate extremes, in particular when data display dependence at observable levels, but are independent in the limit. We propose a flexible class of models that is suitable for such data in a spatial context. In addition, we consider the situation where the extremal dependence structure may vary with distance. We apply our models to spatially referenced significant wave height data from the North Sea, finding evidence that their extremal structure is not compatible with a limiting dependence model. Copyright 2012, Oxford University Press.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Statistical Modeling of Spatial Extremes
Davison, A. C., Padoan, S. A., & Ribatet, M. (2012) · Statistical Science · doi:10.1214/11-sts376 · Cited by 578
Estimating concurrent climate extremes: A conditional approach
Huang, W. K., Monahan, A. H., & Zwiers, F. W. (2021) · Weather and Climate Extremes · doi:10.1016/j.wace.2021.100332 · Cited by 23
Metadata
- Authors
- Wadsworth, J. L., & Tawn, J. A.
- Venue
- Biometrika
- Publisher
- Oxford University Press (OUP)
- Published
- 2012-03-13
- Volume
- 99
- Issue
- 2
- Pages
- 253-272
- ISSN
- 0006-3444 (ISSN-L)
- 1464-3510
- OpenAlex
- W2107439800
- Cited by
- 172
- References
- 0
- FWCI
- 15.12
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Dependence modelling for spatial extremes. https://app.cochat.ai/papers/10.1093/biomet/asr080
- The paper
- Wadsworth, J. L., & Tawn, J. A. (2012). Dependence modelling for spatial extremes. Biometrika. https://doi.org/10.1093/biomet/asr080
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.