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POPInf: Assumption-Lean and Data-Adaptive Post-Prediction Inference

Implementation of assumption-lean and data-adaptive post-prediction inference (POPInf), for valid and efficient statistical inference based on data predicted by machine learning. See Miao, Miao, Wu, Zhao, and Lu (2023) <doi:10.48550/arXiv.2311.14220>.

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: randomForest, MASS
Published: 2024-02-20
DOI: 10.32614/CRAN.package.POPInf
Author: Jiacheng Miao ORCID iD [aut, cre]
Maintainer: Jiacheng Miao <jiacheng.miao at wisc.edu>
License: GPL-3
URL: https://arxiv.org/abs/2311.14220, https://github.com/qlu-lab/POPInf
NeedsCompilation: no
Materials: README
CRAN checks: POPInf results

Documentation:

Reference manual: POPInf.pdf

Downloads:

Package source: POPInf_1.0.0.tar.gz
Windows binaries: r-devel: POPInf_1.0.0.zip, r-release: POPInf_1.0.0.zip, r-oldrel: POPInf_1.0.0.zip
macOS binaries: r-release (arm64): POPInf_1.0.0.tgz, r-oldrel (arm64): POPInf_1.0.0.tgz, r-release (x86_64): POPInf_1.0.0.tgz, r-oldrel (x86_64): POPInf_1.0.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=POPInf to link to this page.

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.