Maximum likelihood estimation for the Fréchet distribution based on block maxima extracted from a time series

DOI10.3150/16-BEJ903zbMath1414.62354arXiv1511.07613OpenAlexW2174764961MaRDI QIDQ2405224

Johan Segers, Axel Bücher

Publication date: 21 September 2017

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1511.07613

zbMATH Keywords

asymptotic normalitymaximum likelihood estimationheavy tailstriangular arraysstationary time seriesblock maxima method

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Point estimation (62F10) Extreme value theory; extremal stochastic processes (60G70)

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Consistency of Bayesian inference for multivariate max-stable distributions ⋮ Estimation of cluster functionals for regularly varying time series: runs estimators ⋮ Multiple block sizes and overlapping blocks for multivariate time series extremes ⋮ Maximum likelihood estimators based on the block maxima method ⋮ On the maximum likelihood estimator for the generalized extreme-value distribution ⋮ Strong convergence of multivariate maxima ⋮ Modeling panels of extremes ⋮ On the disjoint and sliding block maxima method for piecewise stationary time series ⋮ Inference for heavy tailed stationary time series based on sliding blocks ⋮ On second order conditions in the multivariate block maxima and peak over threshold method ⋮ The coupling method in extreme value theory ⋮ Estimation of cluster functionals for regularly varying time series: sliding blocks estimators ⋮ A horse race between the block maxima method and the peak-over-threshold approach

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