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We propose a residual and wild bootstrap methodology for individual and simultaneous inference in high-dimensional linear models with possibly non-Gaussian and heteroscedastic errors.
Limit theorems for regressions with unequal and dependent errors
Eicker, F. (1967) · 1967
Earlier work this paper cites.
The behavior of maximum likelihood estimates under nonstandard conditions
Huber, P. J. (1967) · 1967
Earlier work this paper cites.
Bootstrap methods: Another look at the jackknife
Efron, B. (1979) · 1979
Earlier work this paper cites.
A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity
White, H. (1980) · 1980
Earlier work this paper cites.
Bootstrapping regression models
Freedman, D. A. (1981) · 1981
Earlier work this paper cites.
Jackknife, bootstrap and other resampling methods in regression analysis
Wu, C.-F. J. (1986) · 1986
Earlier work this paper cites.
Necessary conditions for the bootstrap of the mean
Gine, E. and Zinn, J. (1989) · 1989
Earlier work this paper cites.
Bootstrapping general empirical measures
Gine, E. and Zinn, J. (1990) · 1990
Earlier work this paper cites.
Two guidelines for bootstrap hypothesis testing
Hall, P. and Wilson, S. R. (1991) · 1991
Earlier work this paper cites.
Efficiency and robustness in resampling
Liu, R. Y. and Singh, K. (1992) · 1992
Earlier work this paper cites.
Bootstrap and wild bootstrap for high dimensional linear models
Mammen, E. (1993) · 1993
Earlier work this paper cites.
Resampling-based Multiple Testing: Examples and Methods for P-value Adjustment
Westfall, P. and Young, S. (1993) · 1993
Earlier work this paper cites.
Heuristics of instability and stabilization in model selection
Breiman, L. (1996) · 1996
Earlier work this paper cites.
Efficient and Adaptive Estimation for Semiparametric Models
Bickel, P., Klaassen, C., Ritov, Y., and Wellner, J. (1998) · 1998
Earlier work this paper cites.
High-dimensional graphs and variable selection with the Lasso
Meinshausen, N. and Bühlmann, P. (2006) · 2006
Earlier work this paper cites.
The sparsity and bias of the Lasso selection in high-dimensional linear regression
Zhang, C.-H. and Huang, J. (2008) · 2008
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P-values for high-dimensional regression
Meinshausen, N., Meier, L., and Bühlmann, P. (2009) · 2009
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High dimensional variable selection
Wasserman, L. and Roeder, K. (2009) · 2009
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Stability Selection (with discussion)
Meinshausen, N. and Bühlmann, P. (2010) · 2010
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Rate minimaxity of the Lasso and Dantzig selector for the ℓ q \ell_{q} loss in ℓ r \ell_{r} balls
Ye, F. and Zhang, C.-H. (2010) · 2010
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Statistics for High-Dimensional Data: Methods, Theory and Applications
Bühlmann, P. and van de Geer, S. (2011) · 2011
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High-dimensional statistics with a view towards applications in biology
Bühlmann, P., Kalisch, M., and Meier, L. (2014) · 2014
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Confidence intervals and hypothesis testing for high-dimensional regression
Javanmard, A. and Montanari, A. (2014) · 2014
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On asymptotically optimal confidence regions and tests for high-dimensional models
van de Geer, S., Bühlmann, P., Ritov, Y., and Dezeure, R. (2014) · 2014
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Confidence intervals for low dimensional parameters in high dimensional linear models
Zhang, C.-H. and Zhang, S. S. (2014) · 2014
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Monte Carlo Simulation for Lasso-Type Problems by Estimator Augmentation
Zhou, Q. (2014) · 2014
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High-dimensional inference in misspecified linear models
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Bootstrapping Lasso estimators
Chatterjee, A. and Lahiri, S. (2011) · 2011
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Asymptotic optimality of the Westfall-Young permutation procedure for multiple testing under dependence
Meinshausen, N., Maathuis, M. H., and Bühlmann, P. (2011) · 2011
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The adaptive and the thresholded Lasso for potentially misspecified models (and a lower bound for the Lasso)
van de Geer, S., Bühlmann, P., and Zhou, S. (2011) · 2011
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Statistical significance in high-dimensional linear models
Bühlmann, P. (2013) · 2013
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Rates of convergence of the adaptive LASSO estimators to the oracle distribution and higher order refinements by the bootstrap
Chatterjee, A. and Lahiri, S. (2013) · 2013
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Gaussian approximations and multiplier bootstrap for maxima of sums of high-dimensional random vectors
Chernozhukov, V., Chetverikov, D., and Kato, K. (2013) · 2013
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Bühlmann, P. and van de Geer, S. (2015) · 2015
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High-dimensional inference: Confidence intervals, p p -values and R-software hdi
Dezeure, R., Bühlmann, P., Meier, L., and Meinshausen, N. (2015) · 2015
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An Adaptive Resampling Test for Detecting the Presence of Significant Predictors
McKeague, I. W. and Qian, M. (2015) · 2015
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Group bound: confidence intervals for groups of variables in sparse high dimensional regression without assumptions on the design
Meinshausen, N. (2015) · 2015
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Goodness of fit tests for high-dimensional models
Shah, R. and Bühlmann, P. (2015) · 2015
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hdi: High-Dimensional Inference
Meier, L., Dezeure, R., Meinshausen, N., Mächler, M., and Bühlmann, P. (2016) · 2016
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A study of error variance estimation in lasso regression
Reid, S., Tibshirani, R., and Friedman, J. (2016) · 2016
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Simultaneous inference for high-dimensional linear models
Zhang, X. and Cheng, G. (2016) · 2016
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Controlling the false discovery rate via knockoffs
Foygel Barber, R. and Candès, E. J. (2015) · 2085
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