A Bayesian semi-parametric mixture model for bivariate extreme value analysis with application to precipitation forecasting

DOI10.5705/ss.202018.0420zbMath1476.62241OpenAlexW3037874236MaRDI QIDQ5155203

Yuan Tian, Brian J. Reich

Publication date: 6 October 2021

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.5705/ss.202018.0420

zbMATH Keywords

hierarchical modeltail dependencegeneralized Pareto distributionbivariate extreme value model

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Estimation in multivariate analysis (62H12) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to environmental and related topics (62P12) Statistics of extreme values; tail inference (62G32)

Related Items (1)

A restricted four-parameter IRT model: the dyad four-parameter normal ogive (Dyad-4PNO) model

Uses Software

• BayesDA

Cites Work

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