Small-sample likelihood inference in extreme-value regression models

DOI10.1080/00949655.2012.720686zbMath1453.62486arXiv1204.3949OpenAlexW2963460254WikidataQ57496476 ScholiaQ57496476MaRDI QIDQ5219283

Eliane C. Pinheiro, Silvia L. P. Ferrari

Publication date: 9 March 2020

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

Full work available at URL: https://arxiv.org/abs/1204.3949

zbMATH Keywords

likelihood ratio testnonlinear modelsscore testWald testGumbel distributiongradient testsmall-sample adjustmentsextreme-value regression

Mathematics Subject Classification ID

Statistics of extreme values; tail inference (62G32) General nonlinear regression (62J02)

Related Items (4)

Small-sample one-sided testing in extreme value regression models ⋮ Improved hypothesis testing in a general multivariate elliptical model ⋮ Influence diagnostics and model validation for the generalized extreme-value nonlinear regression model ⋮ A comparative review of generalizations of the Gumbel extreme value distribution with an application to wind speed data

Uses Software

• Ox

Cites Work

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• Bias and skewness in a general extreme-value regression model
• Skovgaard's adjustment to likelihood ratio tests in exponential family nonlinear models
• Statistical tools for nonlinear regression. A practical guide with S-PLUS and R examples.
• Likelihood Asymptotics
• Improved likelihood inference in beta regression
• Smooth tail-index estimation
• An introduction to statistical modeling of extreme values

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