Results 321 to 330 of about 4,122,773 (336)

U-Statistics on the Spherical Poisson Space

2016
We review a recent stream of research on normal approximations for linear functionals and more general U-statistics of wavelets/needlets coefficients evaluated on a homogeneous spherical Poisson field. We show how, by exploiting results from Peccati and Zheng (Electron J Probab 15(48):1487–1527, 2010) based on Malliavin calculus and Stein’s method, it ...
Bourguin, Solesne, Durastanti, Claudio, Marinucci, Domenico, Peccati, Giovanni   +3 more
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U-statistics of a bootstrap sample

Ukrainian Mathematical Journal, 1990
Asymptotics of distributions for bootstrapped U-statistis is considered. Conditions for convergence to the normal distribution are indicated.
V. S. Korolyuk, Yu. V. Borovskikh
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U-statistics for skewness or symmetry

Communications in Statistics - Theory and Methods, 1978
We propose certain U-statistics as intuitively reasonable measures of skewness and as criteria for asymptotically distribution-free tests of symmetry. Some comparisons are made with the moment-skewness b1 in terms of small-sample power and asymptotic relative efficiency.
Dana Quade, C.E. Davis
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On U-statistics with random kernels

Statistics & Probability Letters, 1997
Abstract This paper provides conditions under which a U-statistic with a random kernel can be approximated by a U-statistic with a nonstochastic kernel and demonstrates their applicability by means of an example.
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Some asymptotics for U-statistics

Communications in Statistics - Theory and Methods, 1988
We consider a one-sample U-statistic with kernel of dimension 2. We obtain its asymptotic bias and skewness and its Edgeworth and Cornish-Fisher type expansions. We also consider in less detail the one sample U-statistic with kernel of arbitrary dimension.
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Fast surrogates of U-statistics

Computational Statistics & Data Analysis, 2010
U-statistics have long been known as a class of nonparametric estimators with good theoretical properties such as unbiasedness and asymptotic normality. However, their applications in modern statistical analysis are limited due to the high computational complexity, especially when massive data sets are becoming more and more common nowadays.
Nan Lin, Ruibin Xi
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U-statistics in danach spaces

Acta Applicandae Mathematicae, 1994
U-statistics in Banach spaces are considered and thoroughly investigated. The martingale structure, estimates of moments, the law of large numbers, the central limit theorem, the invariance principle, estimates of the rate of convergence, and large deviations are ...
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On estimating the variance of a U-statistic

Communications in Statistics - Theory and Methods, 1985
We compare jackknifing and bootstrapping as methods for estimating the variance of a U-statistic. The use of these estimates in calculating asymptotic confidence intervals is discussed, and the results of a numerical study involving Kendall's tau are reported. For the special case of this statistic, the bootstrap is the estimate of choice.
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Weighted bootstrapping of U-statistics

Journal of Statistical Planning and Inference, 1994
Abstract We introduce a generalized bootstrap procedure for U -statistics. The idea is to reweight the terms of the original U -statistic by stochastic weights. Specific choices of the weights lead to well-known resampling schemes including Efron's bootstrap and Bayesian bootstrap.
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Mm-estimators and U-statistics

2018
M-estimators, and their general versions Mm-estimators, were introduced by Huber (1964) out of robustness considerations. The literature on these estimators is very rich and the asymptotic properties of these estimates have been treated under different sets of conditions.
Arup Bose, Snigdhansu Chatterjee
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