Package: epsiwal 0.1.0

epsiwal: Exact Post Selection Inference with Applications to the Lasso

Implements the conditional estimation procedure of Lee, Sun, Sun and Taylor (2016) <doi:10.1214/15-AOS1371>. This procedure allows hypothesis testing on the mean of a normal random vector subject to linear constraints.

Authors:Steven E. Pav [aut, cre]

epsiwal_0.1.0.tar.gz
epsiwal_0.1.0.zip(r-4.5)epsiwal_0.1.0.zip(r-4.4)epsiwal_0.1.0.zip(r-4.3)
epsiwal_0.1.0.tgz(r-4.5-any)epsiwal_0.1.0.tgz(r-4.4-any)epsiwal_0.1.0.tgz(r-4.3-any)
epsiwal_0.1.0.tar.gz(r-4.5-noble)epsiwal_0.1.0.tar.gz(r-4.4-noble)
epsiwal_0.1.0.tgz(r-4.4-emscripten)epsiwal_0.1.0.tgz(r-4.3-emscripten)
epsiwal.pdf |epsiwal.html✨
epsiwal/json (API)

# Install 'epsiwal' in R:
install.packages('epsiwal', repos = c('https://shabbychef.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/shabbychef/epsiwal/issues

On CRAN:

Conda:

3.18 score 1 stars 1 packages 5 scripts 247 downloads 3 exports 0 dependencies

Last updated 3 years agofrom:12c0661ddf. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 28 2025
R-4.5-winOKMar 28 2025
R-4.5-macOKMar 28 2025
R-4.5-linuxOKMar 28 2025
R-4.4-winOKMar 28 2025
R-4.4-macOKMar 28 2025
R-4.4-linuxOKMar 28 2025
R-4.3-winOKMar 28 2025
R-4.3-macOKMar 28 2025

Exports:ci_connormpconnormptruncnorm

Dependencies: