Package: EAinference
Type: Package
Title: Estimator Augmentation and Simulation-Based Inference
Version: 0.2.3
Authors@R: c(person("Seunghyun", "Min", email = "seunghyun@ucla.edu", role = c("aut", "cre")), person("Qing", "Zhou", email = "zhou@stat.ucla.edu", role = "aut"))
Maintainer: Seunghyun Min <seunghyun@ucla.edu>
Description: Estimator augmentation methods for statistical inference on high-dimensional data, 
    as described in Zhou, Q. (2014) <arXiv:1401.4425v2>
    and Zhou, Q. and Min, S. (2017) <doi:10.1214/17-EJS1309>.
    It provides several simulation-based inference methods: (a) Gaussian and 
    wild multiplier bootstrap for lasso, group lasso, scaled lasso, scaled group
    lasso and their de-biased estimators, (b) importance sampler for approximating
    p-values in these methods, (c) Markov chain Monte Carlo lasso sampler with 
    applications in post-selection inference.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.2.3)
Imports: stats, graphics, msm, mvtnorm, parallel, limSolve, MASS, hdi,
        Rcpp
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2017-12-01 23:11:51 UTC; seunghyunmin
Author: Seunghyun Min [aut, cre],
  Qing Zhou [aut]
Repository: CRAN
Date/Publication: 2017-12-02 00:01:31 UTC
Built: R 4.3.3; x86_64-w64-mingw32; 2025-04-07 02:24:13 UTC; windows
Archs: x64
