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Simple Formula for Mixing Estimators With Different Convergence Rates

Journal of the American Statistical Association, 2015-12, Vol.110 (512), p.1463-1478

2015

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Depth functions as measures of representativeness

Statistical papers (Berlin, Germany), 2014-11, Vol.55 (4), p.1079-1105

2014

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Estimation of central shapes of error distributions in linear regression problems

Annals of the Institute of Statistical Mathematics, 2013-02, Vol.65 (1), p.105-124

2013

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BOOTSTRAP CONFIDENCE REGIONS BASED ON M-ESTIMATORS UNDER NONSTANDARD CONDITIONS

The Annals of statistics, 2020-02, Vol.48 (1), p.274-299

2020

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Hybrid confidence regions based on data depth

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2012, Vol.74 (1), p.91-109

Lee, Stephen M. S.

2012

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A modified Nadaraya-Watson procedure for variable selection and nonparametric prediction with missing data

Journal of nonparametric statistics, 2024-07, Vol.36 (3), p.825-862

2024

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On m out of n Bootstrapping for Nonstandard M-Estimation With Nuisance Parameters

Journal of the American Statistical Association, 2006-09, Vol.101 (475), p.1185-1197

2006

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Double block bootstrap confidence intervals for dependent data

Biometrika, 2009-06, Vol.96 (2), p.427-443

2009

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Iterated Smoothed Bootstrap Confidence Intervals for Population Quantiles

The Annals of statistics, 2005-02, Vol.33 (1), p.437-462

2005

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Bootstrap variance estimation for Nadaraya quantile estimator

Test (Madrid, Spain), 2010-05, Vol.19 (1), p.131-145

2010

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Consistency of a hybrid block bootstrap for distribution and variance estimation for sample quantiles of weakly dependent sequences

Australian & New Zealand journal of statistics, 2018-03, Vol.60 (1), p.103-114

2018

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A recentred bootstrap procedure for constructing uniformly correct confidence sets under smooth function models

Statistics (Berlin, DDR), 2017-03, Vol.51 (2), p.277-293

2017

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Stochastically optimal bootstrap sample size for shrinkage-type statistics

Statistics and computing, 2016-01, Vol.26 (1-2), p.249-262

2016

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Importance of interpolation when constructing double-bootstrap confidence intervals

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2000, Vol.62 (2), p.479-491

2000

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Calibrated interpolated confidence intervals for population quantiles

Biometrika, 2005-03, Vol.92 (1), p.234-241

2005

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Iterated Bootstrap-t Confidence Intervals for Density Functions

Scandinavian journal of statistics, 2008-06, Vol.35 (2), p.295-308

2008

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Prepivoting by weighted bootstrap iteration

Biometrika, 2003-06, Vol.90 (2), p.393-410

2003

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Robustness Diagnosis for Bootstrap Inference

Journal of computational and graphical statistics, 2011-06, Vol.20 (2), p.448-460

2011

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Second-order accuracy of depth-based bootstrap confidence regions

Journal of multivariate analysis, 2012-02, Vol.105 (1), p.112-123

2012

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High-dimensional local polynomial regression with variable selection and dimension reduction

Statistics and computing, 2024-02, Vol.34 (1), Article 1

2024

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Optimal Bootstrap Sample Size in Construction of Percentile Confidence Bounds

Scandinavian journal of statistics, 2001-03, Vol.28 (1), p.225-239

2001

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High–dimensional local linear regression under sparsity and convex losses

Electronic journal of statistics, 2024-01, Vol.18 (1)

2024

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Asymptotic Iterated Bootstrap Confidence Intervals

The Annals of statistics, 1995-08, Vol.23 (4), p.1301-1330

1995

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A new statistical depth function with applications to multimodal data

Journal of nonparametric statistics, 2011-09, Vol.23 (3), p.617-631

2011

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An Overview of Asymptotic Properties of Lp Regression Under General Classes of Error Distributions

Journal of the American Statistical Association, 2005-06, Vol.100 (470), p.446-458

2005

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Simple Formula for Mixing Estimators With Different Convergence Rates

Depth functions as measures of representativeness

Estimation of central shapes of error distributions in linear regression problems

BOOTSTRAP CONFIDENCE REGIONS BASED ON M-ESTIMATORS UNDER NONSTANDARD CONDITIONS

Hybrid confidence regions based on data depth

A modified Nadaraya-Watson procedure for variable selection and nonparametric prediction with missing data

On m out of n Bootstrapping for Nonstandard M-Estimation With Nuisance Parameters

Double block bootstrap confidence intervals for dependent data

Iterated Smoothed Bootstrap Confidence Intervals for Population Quantiles

Bootstrap variance estimation for Nadaraya quantile estimator

Consistency of a hybrid block bootstrap for distribution and variance estimation for sample quantiles of weakly dependent sequences

A recentred bootstrap procedure for constructing uniformly correct confidence sets under smooth function models

Stochastically optimal bootstrap sample size for shrinkage-type statistics

Importance of interpolation when constructing double-bootstrap confidence intervals

Calibrated interpolated confidence intervals for population quantiles

Iterated Bootstrap-t Confidence Intervals for Density Functions

Prepivoting by weighted bootstrap iteration

Robustness Diagnosis for Bootstrap Inference

Second-order accuracy of depth-based bootstrap confidence regions

High-dimensional local polynomial regression with variable selection and dimension reduction

Optimal Bootstrap Sample Size in Construction of Percentile Confidence Bounds

High–dimensional local linear regression under sparsity and convex losses

Asymptotic Iterated Bootstrap Confidence Intervals

A new statistical depth function with applications to multimodal data

An Overview of Asymptotic Properties of Lp Regression Under General Classes of Error Distributions

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