CRAN/E | EAinference

EAinference

Estimator Augmentation and Simulation-Based Inference

Installation

About

Estimator augmentation methods for statistical inference on high-dimensional data, as described in Zhou, Q. (2014) 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.

Key Metrics

Version 0.2.3
R ≥ 3.2.3
Published 2017-12-02 2326 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks EAinference results

Downloads

Yesterday 1
Last 7 days 17 -59%
Last 30 days 157 -4%
Last 90 days 720 +41%
Last 365 days 2.331 -27%

Maintainer

Maintainer

Seunghyun Min

seunghyun@ucla.edu

Authors

Seunghyun Min

aut / cre

Qing Zhou

aut

Material

Reference manual
Package source

Vignettes

Introduction to EAinference

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

EAinference archive

Depends

R ≥ 3.2.3

Imports

stats
graphics
msm
mvtnorm
parallel
limSolve
MASS
hdi
Rcpp

Suggests

knitr
rmarkdown
testthat

LinkingTo

Rcpp
RcppArmadillo