Tail fitting for truncated and non-truncated Pareto-type distributions
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Publication:508715
DOI10.1007/S10687-016-0247-3zbMath1360.62244arXiv1505.05189OpenAlexW1795962610MaRDI QIDQ508715
Ivette Gomes, Jan Beirlant, M. Isabel Fraga Alves
Publication date: 8 February 2017
Published in: Extremes (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1505.05189
Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Statistics of extreme values; tail inference (62G32) Probability distributions: general theory (60E05)
Related Items (10)
Handling missing extremes in tail estimation ⋮ Using jackknife to correct bias of MLE for the truncated Pareto distribution ⋮ Modelling censored losses using splicing: a global fit strategy with mixed Erlang and extreme value distributions ⋮ A discrete truncated Zipf distribution ⋮ EXTREME VALUE ANALYSIS WITHOUT THE LARGEST VALUES: WHAT CAN BE DONE? ⋮ TEMPERED PARETO-TYPE MODELLING USING WEIBULL DISTRIBUTIONS ⋮ Introduction to extreme value theory: applications to risk analysis and management ⋮ Data-adaptive trimming of the Hill estimator and detection of outliers in the extremes of heavy-tailed data ⋮ Robust quantile estimation under bivariate extreme value models ⋮ Estimating the second-order parameter of regular variation and bias reduction in tail index estimation under random truncation
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