Estimator augmentation methods for statistical inference on highdimensional data, as described in Zhou, Q. (2014) <arXiv:1401.4425v2> and Zhou, Q. and Min, S. (2017) <doi:10.1214/17EJS1309>. It provides several simulationbased inference methods: (a) Gaussian and wild multiplier bootstrap for lasso, group lasso, scaled lasso, scaled group lasso and their debiased estimators, (b) importance sampler for approximating pvalues in these methods, (c) Markov chain Monte Carlo lasso sampler with applications in postselection inference.
Package details 


Author  Seunghyun Min [aut, cre], Qing Zhou [aut] 
Maintainer  Seunghyun Min <seunghyun@ucla.edu> 
License  GPL (>= 2) 
Version  0.2.3 
Package repository  View on CRAN 
Installation 
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