Fast parameter estimation of generalized extreme value distribution using neural networks

DOI10.1002/env.2845zbMATH Open1548.62521MaRDI QIDQ6626658

Stephan R. Sain, Soutir Bandyopadhyay, Alexis Hoffman, Soumendra N. Lahiri, Sweta Rai, Douglas Nychka

Publication date: 28 October 2024

Published in: Environmetrics (Search for Journal in Brave)

zbMATH Keywords

parameter estimationsufficient statisticsgeneralized extreme value distributionextreme quantilesdeep neural networks

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12)

Cites Work

• Unnamed Item
• On the maximum likelihood estimator for the generalized extreme-value distribution
• Likelihood-based inference for extreme value model
• A full Bayesian approach to generalized maximum likelihood estimation of generalized extreme value distribution
• Practical extreme value modelling of hydrological floods and droughts: a case study
• Bayesian Spatial Modeling of Extreme Precipitation Return Levels
• Maximum likelihood estimation in a class of nonregular cases
• Learning Summary Statistic for Approximate Bayesian Computation via Deep Neural Network
• Likelihood-Based Inference for Max-Stable Processes
• An introduction to statistical modeling of extreme values
• Statistical modeling of spatial extremes
• Neural networks for parameter estimation in intractable models
• Fast covariance parameter estimation of spatial Gaussian process models using neural networks
• Likelihood-Free Parameter Estimation with Neural Bayes Estimators
• Advances in statistical modeling of spatial extremes
• A flexible extended generalized Pareto distribution for tail estimation

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