Results 11 to 20 of about 1,023,504 (281)
Direct Reduction of Bias of the Classical Hill Estimator [PDF]
Revstat Statistical Journal, 2005 In this paper we are interested in an adequate estimation of the dominant component of the bias of Hill’s estimator of a positive tail index γ, in order to remove it from the classical Hill estimator in different asymptotically equivalent ways.
Frederico Caeiro +2 more
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Location invariant Weiss-Hill estimator [PDF]
Extremes, 2011 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ling, Chengxiu +2 more
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Adapting the Hill estimator to distributed inference: dealing with the bias [PDF]
Extremes, 2022 The distributed Hill estimator is a divide-and-conquer algorithm for estimating the extreme value index when data are stored in multiple machines. In applications, estimates based on the distributed Hill estimator can be sensitive to the choice of the number of the exceedance ratios used in each machine.
Liujun Chen, Deyuan Li, Chen Zhou
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Smoothing the Hill Estimator [PDF]
Advances in Applied Probability, 1997 For sequences of i.i.d. random variables whose common tail 1 –Fis regularly varying at infinity wtih an unknown index –α< 0, it is well known that the Hill estimator is consistent for α–1and usually asymptotically normally distributed. However, because the Hill estimator is a function ofk = k(n), the number of upper order statistics used and which ...
Resnick, Sidney, Stărică, Cătălin
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Estimating and comparing microbial diversity in the presence of sequencing errors [PDF]
PeerJ, 2016 Estimating and comparing microbial diversity are statistically challenging due to limited sampling and possible sequencing errors for low-frequency counts, producing spurious singletons. The inflated singleton count seriously affects statistical analysis
Chun-Huo Chiu, Anne Chao
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Revstat Statistical Journal, 2011 Sousa and Michailidis (2004) developed the sum plot based on the Hill (1975) estimator as a diagnostic tool for selecting the optimal k when the distribution is heavy tailed.
J. Beirlant , E. Boniphace , G. Dierckx
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A Couple of Non Reduced Bias Generalized Means in Extreme Value Theory
Revstat Statistical Journal, 2020 Lehmer’s mean-of-order p (Lp) generalizes the arithmetic mean, and Lp extreme value index (EVI)-estimators can be easily built, as a generalization of the classical Hill EVI-estimators. Apart from a reference to the asymptotic behaviour of this class of
Helena Penalva +3 more
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Tail prepivoting for the Hill estimator [PDF]
Journal of Physics A: Mathematical and Theoretical, 2016 It is well known that prepivoting reduces level error of confidence sets. We adapt this method to the context of the tail index estimation, introducing a procedure that we call tail prepivoting. We apply this procedure to the Hill estimator and establish its consistency.
Margarida Brito +2 more
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Estimation of heavy tails in optical non-linear processes
New Journal of Physics, 2021 In optical non-linear processes, rogue waves can be observed, which can be mathematically described by heavy-tailed distributions. These distributions are special since the probability of registering extremely high intensities is significantly higher ...
Éva Rácz +2 more
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Improvements in the Estimation of a Heavy Tail
Revstat Statistical Journal, 2006 In this paper, and in a context of regularly varying tails, we suggest new tail index estimators, which provide interesting alternatives to the classical Hill estimator of the tail index γ.
Orlando Oliveira +2 more
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