DebiasInfer
Efficient Inference on High-Dimensional Linear Model with Missing Outcomes
A statistically and computationally efficient debiasing method for conducting valid inference on the high-dimensional linear regression function with missing outcomes. The reference paper is Zhang, Giessing, and Chen (2023) <doi:10.48550/arXiv.2309.06429>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.2.1 |
rolling linux/jammy R-4.5 | DebiasInfer_0.2.1.tar.gz |
34.6 KiB |
0.2.1 |
rolling linux/noble R-4.5 | DebiasInfer_0.2.1.tar.gz |
34.6 KiB |
0.2.1 |
rolling source/ R- | DebiasInfer_0.2.1.tar.gz |
7.0 KiB |
0.2.1 |
latest linux/jammy R-4.5 | DebiasInfer_0.2.1.tar.gz |
34.6 KiB |
0.2.1 |
latest linux/noble R-4.5 | DebiasInfer_0.2.1.tar.gz |
34.6 KiB |
0.2.1 |
latest source/ R- | DebiasInfer_0.2.1.tar.gz |
7.0 KiB |
0.2.1 |
2026-04-26 source/ R- | DebiasInfer_0.2.1.tar.gz |
7.0 KiB |
0.2.1 |
2026-04-23 source/ R- | DebiasInfer_0.2.1.tar.gz |
7.0 KiB |
0.2.1 |
2026-04-09 windows/windows R-4.5 | DebiasInfer_0.2.1.zip |
37.9 KiB |
0.2 |
2025-04-20 source/ R- | DebiasInfer_0.2.tar.gz |
12.0 KiB |