Results 261 to 270 of about 1,023,504 (281)

Weiss-Hill estimator

Test, 2001
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Reduced bias Hill estimators

AIP Conference Proceedings, 2016
For heavy tails, classical extreme value index estimators, like the Hill estimator, are usually asymptotically biased. Consequently those estimators are quite sensitive to the number of top order statistics used in the estimation. The recent minimum-variance reduced-bias extreme value index estimators enable us to remove the dominant component of ...
Ivanilda Cabral, Frederico Caeiro, M. Ivette Gomes   +2 more
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A Location Invariant Hill-Type Estimator

Extremes, 2001
A new estimator, under a semiparametric approach, which behaves similarly to Hill's estimator, see \textit{B.M. Hill}, Ann. Stat. 3, 1163--1174 (1975; Zbl 0323.62033), but which is invariant to location transformations, is studied. Let \(X_1,X_2,\ldots,X_ n\) be independent random variables with common distribution function \(F\) and let \(X_{(1,n)},X_{
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Effect of Eye Height on Estimated Slopes of Hills

Perception, 2015
Several studies have shown that slopes of hills are greatly overestimated. We have recently demonstrated that the overestimates increase logarithmically as the end point of the domain to be estimated is increased. A theoretical analysis showed that a critical parameter is the angle between the observer’s line of sight and the slope of the hill, when ...
Bruce, Bridgeman, Ian, Cooke
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Asymptotic Normality of Hill’s Estimator

1989
Hill’s estimator has been shown to be very useful in tail and quantile estimation. In an earlier paper the authors found a broad class of underlying distributions such that Hill’s estimator is asymptotically normal. In this note the domain of attraction of the normal law is further specified.
Jan Beirlant, Jozef L. Teugels
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SHIFTED HILL'S ESTIMATOR FOR HEAVY TAILS

Communications in Statistics - Simulation and Computation, 2001
Hill's estimator is a popular method for estimating the thickness of heavy tails. In this paper we modify Hill's estimator to make it shift-invariant as well as scale-invariant. The resulting shifted Hill's estimator is a more robust method of estimating tail thickness. †Partially supported by NSF-EAR grant 9980484.
Inmaculada B. Aban, Mark M. Meerschaert1†   +1 more
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Weak Convergence of the Hill Estimator Process

1994
Let X 1 X 2,…, be a sequence of nonnegative i. i. d. random variables and for each n ≥ 1 let X 1, n ≤… ≤ Xn, n denote the order statistics based on the first n of these X’s. The Hill estimator is the sum of extreme values Σi≤kn )/k n , where k n → ∞ and k/ n →0, as n→ ∞.
David M. Mason, Tatyana S. Turova
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Almost sure convergence of the Hill estimator

Mathematical Proceedings of the Cambridge Philosophical Society, 1988
AbstractIn this note we characterize those sequencesknsuch that the Hill estimator of the tail index based on theknupper order statistics of a sample of sizenfrom a Pareto-type distribution is strongly consistent.
Deheuvels, Paul, Haeusler, Erich, Mason, David M.   +2 more
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Large deviation theorem for Hill's estimator

Acta Mathematica Sinica, 1992
Consider a sample of \(n\) i.i.d. random variables on the real line whose common distribution function \(F\) is regularly varying at infinity with unknown index of variation \(1/r\). A popular estimator of \(r\) is \textit{B. M. Hill's} estimator \(r_ n\) [Ann. Stat. 3, No.
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Asymptotic behavior of Hill's estimate and applications

Journal of Applied Probability, 1986
The problem of estimating the exponent of a stable law is receiving an increasing amount of attention because Pareto's law (or Zipf's law) describes many biological phenomena very well (see e.g. Hill (1974)). This problem was first solved by Hill (1975), who proposed an estimate, and the convergence of that estimate to some positive and finite number ...
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