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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.

Version: 0.1.0
Depends: R (≥ 3.0.2)
Suggests: testthat
Published: 2019-07-02
Author: Steven E. Pav ORCID iD [aut, cre]
Maintainer: Steven E. Pav <shabbychef at gmail.com>
BugReports: https://github.com/shabbychef/epsiwal/issues
License: LGPL-3
URL: https://github.com/shabbychef/epsiwal
NeedsCompilation: no
Citation: epsiwal citation info
Materials: README ChangeLog
CRAN checks: epsiwal results

Documentation:

Reference manual: epsiwal.pdf

Downloads:

Package source: epsiwal_0.1.0.tar.gz
Windows binaries: r-devel: epsiwal_0.1.0.zip, r-release: epsiwal_0.1.0.zip, r-oldrel: epsiwal_0.1.0.zip
macOS binaries: r-release (arm64): epsiwal_0.1.0.tgz, r-oldrel (arm64): epsiwal_0.1.0.tgz, r-release (x86_64): epsiwal_0.1.0.tgz, r-oldrel (x86_64): epsiwal_0.1.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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