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 |
| Author: | Jiacheng Miao 
[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.