Results 201 to 210 of about 8,231 (239)

When Cluster-Robust Inferences Fail. [PDF]

Educ Psychol Meas
Huang F.
europepmc   +1 more source

CRT-Estimands Framework: consensus based extension of the ICH E9(R1) addendum for cluster randomised trials.

BMJ
Kahan BC, Bretz F, Copas A, Harhay MO, Collins GS, Bahti M, Bi D, Campbell MK, Courtright KR, Feeney T, Forbes AB, Garg AX, Halpern SD, Heagerty PJ, Hemming K, Hopewell S, Hughes JP, Murray DM, Ross JS, Stewart D, Taljaard M, Ukoumunne OC, Auriemma CL, Li F.   +23 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Approximation of the Hill estimator process

Statistics and Probability Letters, 1998
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
R -D Reiss
exaly   +2 more sources

Abelian and Tauberian Theorems on the Bias of the Hill Estimator

Scandinavian Journal of Statistics, 2002
The bias of Hill's estimator for the positive extreme value index of a distribution is investigated in relation to the convergence rate in the regular variation property of the tail function of the common distribution of the sample and the corresponding tail quantile function.
Johan Segers
exaly   +3 more sources

Some results on the behaviour of hill’s estimator

Journal of Statistical Computation and Simulation, 1999
The maximum of a large number of random variables, suitably normalized, follows, under certain general conditions, the Generalized Extreme Value (GEV) distribution . Hill’s estimator provides an estimation for γ > 0 from a finite sample, requiring the largest m observations, out of n.
M Ivette Gomes
exaly   +2 more sources

Hill's estimator under weak dependence

Communications in Statistics - Theory and Methods, 2017
ABSTRACTIn this article, we investigate the asymptotic normality of the Hill's estimator of the tail index parameter, when the observations are weakly dependent in the sense of Doukhan and Louhichi (1999) and are drawn from a strictly linear process. We show that the previous result on Hill estimator obtained by Rootzen et al.
Karima Boualam, Youcef Berkoun
exaly   +2 more sources

Multivariate Hill Estimators

International Statistical Review, 2015
SummaryWe propose two classes of semi‐parametric estimators for the tail index of a regular varying elliptical random vector. The first one is based on the distance between a tail probability contour and the observations outside this contour. We denote it as the class ofseparatingestimators. The second one is based on the norm of an arbitrary order. We
Dominicy, Yves, Ilmonen, Pauliina, Veredas, David   +3 more
openaire   +1 more source

The Asymptotic Behavior of Hill’s Estimator

Theory of Probability & Its Applications, 1987
See the review in Zbl 0611.62036.
Beirlant, Jan, Teugels, J. K.
openaire   +1 more source

A simple generalisation of the Hill estimator

Computational Statistics & Data Analysis, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Maria de Fátima Brilhante, M. Ivette Gomes, Dinis Pestana   +2 more
openaire   +1 more source