Asymptotic properties of the residual bootstrap for Lasso estimators

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Rates of convergence of the Adaptive LASSO estimators to the Oracle distribution and higher order refinements by the bootstrap (2013, methodology): “Post model selection inference, including the bootstrap and its variants have been investigated by Bach (2009), Chatterjee and Lahiri (2010, 2011a), Minnier, Tian and Cai (2011) and Berk et al. (2013), among others.”
Model confidence bounds for variable selection (2016, background): “For example, Fan and Lv (2010) establish the model selection consistency (as part of the oracle property) as a standard property for many methods. Pötscher and Schneider (2010) and Leeb and Pötscher (2006) have presented similar assumptions in their results. Lastly, Liu and Yu (2013) and Chatterjee ”
Penalized expectile regression: an alternative to penalized quantile regression (2018, methodology): “Also, resampling methods for hypothesis testing have been studied; Chatterjee and Lahiri (2010) apply the residual bootstrap approach to the LASSO estimator, and Minnier et al.”
Bootstrapping Lasso Estimators (2011, methodology): “Properties of the standard bootstrap method have been investigated by Knight and Fu (2000) and Chatterjee and Lahiri (2010), in the same set up.”