Integral distribution-free statistics of \(L_p\)-type and their asymptotic comparison

DOI10.1016/j.csda.2009.02.018zbMath1453.62109OpenAlexW2029346387MaRDI QIDQ961803

Bruno Ebner, Norbert Henze, Yakov Yu. Nikitin

Publication date: 1 April 2010

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2009.02.018

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20)

Related Items (8)

New class of exponentiality tests based on U-empirical Laplace transform ⋮ Asymptotic behavior of weighted multivariate Cramér-von Mises-type statistics under contiguous alternatives ⋮ Cramér-von-Mises tests for the distribution of the excess over a confidence level ⋮ Bahadur efficiencies of the Epps-Pulley test for normality ⋮ Comparison of efficiencies of some symmetry tests around an unknown centre ⋮ A weighted bootstrap approximation of the maximal deviation of kernel density estimates over general compact sets ⋮ Toward the history of the St. Petersburg school of probability and statistics. IV: Characterization of distributions and limit theorems in statistics ⋮ Weighted bootstrapped kernel density estimators in two-sample problems

Uses Software

• sn

Cites Work

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• Large deviations and asymptotic efficiency of a statistic of integral type. II
• On the distributions of \(L_ p\) norms of weighted uniform empirical and quantile processes
• Relative efficiencies of goodness of fit procedures for assessing univariate normality
• A condition under which the Pitman and Bahadur approaches to efficiency coincide
• A distribution free test for the two sample problem for general alternatives
• Goodness-of-fit statistics based on weighted \(L_ p\)-functionals
• Nontraditional approaches to statistical classification: Some perspectives on \(L_ p\)-norm methods
• Nonparametric integral statistics \(\omega_n^k=n^{k/2}\int_{-\infty}^\infty [S_n(x)-F(x)^k dF(x)\): Main properties and applications]
• Local Bahadur efficiency of some goodness-of-fit tests under skew alternatives.
• Rough large-deviation probability asymptotics of some functionals of the norm kind
• The Laplace method for computing exact asymptotics of distributions of integral statistics.
• Definition and probabilistic properties of skew-distributions.
• Tail behavior of anisotropic norms for Gaussian random fields
• Skewed multivariate models related to hidden truncation and/or selective reporting. With discussion and a rejoinder by the authors.
• An \(L_ 1\)-variant of the Cramér-von Mises test
• The law of the iterated logarithm for \(L_ p\)-norms of empirical processes
• Weak convergence of the sample distribution function when parameters are estimated
• On the \(\mathbb L_p\)-error of monotonicity constrained estimators
• Asymptotic Efficiency of Nonparametric Tests
• Problems of inference for Azzalini's skewnormal distribution
• The Relative Efficiency of Goodness-of-Fit Statistics in the Simple and Composite Hypothesis-Testing Problem
• An invariance principle for the law of the iterated logarithm
• The Skew-normal Distribution and Related Multivariate Families*
• Distribution Free Tests of Independence Based on the Sample Distribution Function
• Stochastic Comparison of Tests
• Some approximations toL_p-statistics of kernel density estimators
• Strong laws for \(L_p\)-norms of empirical and related processes

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