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Coverage probability of bootstrap confidence intervals in heavy-tailed frequency models, with application to precipitation data
- 1.0350698 - ÚFA 2011 RIV AT eng J - Journal Article
Coverage probability of bootstrap confidence intervals in heavy-tailed frequency models, with application to precipitation data.
Theoretical and Applied Climatology. Roč. 101, 3-4 (2010), s. 345-361. ISSN 0177-798X
R&D Projects: GA AV ČR KJB300420801
Institutional research plan: CEZ:AV0Z30420517
Keywords : bootstrap * extreme value analysis * confidence intervals * heavy-tailed distributions * precipitation amounts
Subject RIV: DG - Athmosphere Sciences, Meteorology
Impact factor: 1.684, year: 2010
The paper compares coverage probabilities of confidence intervals of high quantiles (5-yr to 200-yr return values) constructed by the nonparametric and parametric bootstrap in frequency analysis of heavy-tailed data, typical for maxima of precipitation amounts. The simulation experiments are based on a wide range of models used for precipitation extremes (Generalized Extreme Value, Generalized Pareto, Generalized Logistic, and mixed distributions). We show that both bootstrap methods underestimate the width of the confidence intervals but that the parametric bootstrap is clearly superior to the nonparametric one.
Permanent Link: http://hdl.handle.net/11104/0190631