Box–Cox transformations and heavy-tailed distributions

DOI10.1239/jap/1082552200zbMath1048.62053OpenAlexW2042251585MaRDI QIDQ4822462

Giovanni Vanroelen, Jozef L. Teugels

Publication date: 25 October 2004

Published in: Journal of Applied Probability (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1239/jap/1082552200

zbMATH Keywords

heavy-tailed distributionsHill estimatorBox-Cox transformationsecond-order regular variation

Mathematics Subject Classification ID

Statistics of extreme values; tail inference (62G32) Rate of growth of functions, orders of infinity, slowly varying functions (26A12)

Related Items (5)

Accounting for choice of measurement scale in extreme value modeling ⋮ An anti-ideal point representation of economic discrete choice models ⋮ OPTIMAL SEMIPARAMETRIC INFERENCE FOR THE TAIL INDEX BASED ON RATIOS OF THE LARGEST EXTREMES ⋮ Efficiency of t-Test and Hotelling's T ²-Test After Box-Cox Transformation ⋮ Estimation of Extreme Conditional Quantiles Through Power Transformation

Cites Work

• A simple general approach to inference about the tail of a distribution
• Quasi-likelihood and its application. A general approach to optimal parameter estimation
• Tail index estimation and an exponential regression model
• A location invariant Hill-type estimator
• Sur la distribution limite du terme maximum d'une série aléatoire
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