Dynamic linear seasonal models applied to extreme temperature data: a Bayesian approach using the r-larger order statistics distribution

DOI10.1080/00949655.2021.1971668OpenAlexW3198330578MaRDI QIDQ3390581

Marcelo Bourguignon, Fernando Ferraz do Nascimento, Renato Santos da Silva

Publication date: 24 March 2022

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2021.1971668

zbMATH Keywords

Markov chain Monte Carloextreme value theoryBayesiandynamic modelsenvironmental data

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• ismev

Cites Work

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• Estimation of Parameters and Larger Quantiles Based on the k Largest Observations
• Discovering the False Discovery Rate
• Regression models for time-varying extremes
• Bayesian estimation and prediction based on lognormal record values
• A default Bayesian approach for regression on extremes
• Sequential Selection Procedures and False Discovery Rate Control
• An introduction to statistical modeling of extreme values

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