Refinements of the Kiefer-Wolfowitz theorem and a test of concavity
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Publication:2008622
DOI10.1214/19-EJS1638zbMath1434.62037arXiv1906.10305OpenAlexW2985853930MaRDI QIDQ2008622
Publication date: 26 November 2019
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1906.10305
Density estimation (62G07) Nonparametric hypothesis testing (62G10) Nonparametric estimation (62G05)
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Cites Work
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- Distribution-free tests of conditional moment inequalities
- Isotonic \(L_{2}\)-projection test for local monotonicity of a hazard
- A Kiefer-Wolfowitz type of result in a general setting, with an application to smooth monotone estimation
- Distribution-free tests of stochastic monotonicity
- Bootstrap consistency for general semiparametric \(M\)-estimation
- On the uniform asymptotic validity of subsampling and the bootstrap
- On differentiable functionals
- Bootstrapping general empirical measures
- Distribution of global measures of deviation between the empirical distribution function and its concave majorant
- Asymptotic expansions for general statistical models. With the assist. of W. Wefelmeyer
- Monotone nonparametric regression
- Asymptotic analysis of stochastic programs
- Exchangeably weighted bootstraps of the general empirical process
- On nondifferentiable functions and the bootstrap
- A Kolmogorov-type test for monotonicity of regression.
- A conversation with Jon Wellner
- Tests of stochastic monotonicity with improved power
- Testing uniformity versus a monotone density
- On concepts of directional differentiability
- Likelihood ratio tests for monotone functions.
- On the distance between the empirical process and its concave majorant in a monotone regression framework. (Sur la distance entre le processus empirique et son majorant concave dans un modèle de régression monotone)
- Weak convergence and empirical processes. With applications to statistics
- Nonparametric tests for change-point detection à la Gombay and Horváth
- Refinements of the Kiefer-Wolfowitz theorem and a test of concavity
- Weak convergence of the least concave majorant of estimators for a concave distribution function
- Introduction to empirical processes and semiparametric inference
- Nonparametric Estimation under Shape Constraints
- On the Estimation of Parameters Restricted by Inequalities
- ASYMPTOTIC SIZE AND A PROBLEM WITH SUBSAMPLING AND WITH THE m OUT OF n BOOTSTRAP
- Splines (with optimal knots) are better
- Asymptotically minimax estimation of concave and convex distribution functions
- Asymptotic Statistics
- LIMIT THEOREMS FOR ASYMPTOTICALLY MINIMAX ESTIMATION OF A DISTRIBUTION WITH INCREASING FAILURE RATE UNDER A RANDOM MIXED CENSORSHIP/TRUNCATION MODEL
- BLOCK BOOTSTRAP CONSISTENCY UNDER WEAK ASSUMPTIONS
- Inference on Directionally Differentiable Functions
- TESTING REGRESSION MONOTONICITY IN ECONOMETRIC MODELS
- NONPARAMETRIC TESTS OF DENSITY RATIO ORDERING
- Nonparametric tests for and against likelihood ratio ordering in the two-sample problem
- A Kiefer-Wolfowitz theorem for convex densities
- Testing Statistical Hypotheses
- Likelihood Ratio Tests Under Local and Fixed Alternatives in Monotone Function Problems
- A practical guide to splines.
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