An Omnibus Non-Parametric Test of Equality in Distribution for Unknown Functions

DOI10.1111/rssb.12299zbMath1407.62152arXiv1510.04195OpenAlexW2963303442WikidataQ91525759 ScholiaQ91525759MaRDI QIDQ3120101

Mark J. Van der Laan, Alex Luedtke, Marco Carone

Publication date: 1 March 2019

Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1510.04195

zbMATH Keywords

nonparametric testmaximum mean discrepancyequality in distributionomnibus testinfinite dimensional parameterhigher order pathwise differentiability

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20)

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Uses Software

• SuperLearner
• np
• rARPACK

Cites Work

• Unnamed Item
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• Equivalence of distance-based and RKHS-based statistics in hypothesis testing
• Higher order tangent spaces and influence functions
• Statistical methods for dynamic treatment regimes. Reinforcement learning, causal inference, and personalized medicine
• U-processes: Rates of convergence
• Contributions to a general asymptotic statistical theory. With the assistance of W. Wefelmeyer
• Asymptotic expansions for general statistical models. With the assist. of W. Wefelmeyer
• Functional limit theorems for U-processes
• Large sample theory for U-statistics and tests of fit
• A significance test for covariates in nonparametric regression
• 10.1162/153244302760185252
• Testing the Significance of Categorical Predictor Variables in Nonparametric Regression Models
• Higher order influence functions and minimax estimation of nonlinear functionals
• Discrete approximation of integral operators
• Optimal Structural Nested Models for Optimal Sequential Decisions
• Algorithmic Learning Theory
• Super Learner