Crandore Hub

MLBC

Bias Correction Methods for Models Using Synthetic Data

Implements three bias-correction techniques from Battaglia et al. (2025 <doi:10.48550/arXiv.2402.15585>) to improve inference in regression models with covariates generated by AI or machine learning.

Versions across snapshots

VersionRepositoryFileSize
0.2.2 rolling linux/jammy R-4.5 MLBC_0.2.2.tar.gz 603.8 KiB
0.2.2 rolling linux/noble R-4.5 MLBC_0.2.2.tar.gz 611.8 KiB
0.2.2 rolling source/ R- MLBC_0.2.2.tar.gz 147.4 KiB
0.2.2 latest linux/jammy R-4.5 MLBC_0.2.2.tar.gz 603.8 KiB
0.2.2 latest linux/noble R-4.5 MLBC_0.2.2.tar.gz 611.8 KiB
0.2.2 latest source/ R- MLBC_0.2.2.tar.gz 147.4 KiB
0.2.2 2026-04-26 source/ R- MLBC_0.2.2.tar.gz 147.4 KiB
0.2.2 2026-04-23 source/ R- MLBC_0.2.2.tar.gz 147.4 KiB
0.2.2 2026-04-09 windows/windows R-4.5 MLBC_0.2.2.zip 908.8 KiB

Dependencies (latest)

Imports

LinkingTo

Suggests