Asymptotic models and inference for extremes of spatio-temporal data
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Publication:650739
DOI10.1007/s10687-009-0092-8zbMath1226.60083OpenAlexW2157607185WikidataQ58650798 ScholiaQ58650798MaRDI QIDQ650739
Publication date: 27 November 2011
Published in: Extremes (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/10400.5/8098
Inference from spatial processes (62M30) Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15) Extreme value theory; extremal stochastic processes (60G70)
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Uses Software
Cites Work
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- A default Bayesian procedure for the generalized Pareto distribution
- On extremal theory for stationary processes
- Stationary max-stable fields associated to negative definite functions
- Extremes and related properties of random sequences and processes
- Models for stationary max-stable random fields
- On spatial extremes: with application to a rainfall problem
- Spatial extremes: models for the stationary case
- A Hierarchical Model for Extreme Wind Speeds
- Models for dependent extremes using stable mixtures
- Bayesian Spatial Modeling of Extreme Precipitation Return Levels
- A Conditional Approach for Multivariate Extreme Values (with Discussion)
- Likelihood-Based Inference for Max-Stable Processes
- Generalized Additive Modelling of Sample Extremes
- An introduction to statistical modeling of extreme values
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