MetaHunt
Privacy-Preserving Meta-Analysis via Low-Rank Basis Hunting
Tools for privacy-preserving meta-analysis of function-valued quantities across heterogeneous studies. Implements the 'MetaHunt' pipeline, including the denoised functional Successive Projection Algorithm (d-fSPA) for basis hunting, constrained weight estimation, Dirichlet regression of weights on study-level covariates, target prediction, and split/cross conformal prediction intervals. Operates on aggregate-level function evaluations, so individual-level data from source studies are not required. Methodology described in Shi, Imai, and Zhang (2026) <doi:10.48550/arXiv.2604.23847>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | MetaHunt_0.1.0.tar.gz |
553.4 KiB |
0.1.0 |
rolling linux/noble R-4.5 | MetaHunt_0.1.0.tar.gz |
553.3 KiB |
0.1.0 |
rolling source/ R- | MetaHunt_0.1.0.tar.gz |
448.1 KiB |
0.1.0 |
latest linux/jammy R-4.5 | MetaHunt_0.1.0.tar.gz |
553.4 KiB |
0.1.0 |
latest linux/noble R-4.5 | MetaHunt_0.1.0.tar.gz |
553.3 KiB |
0.1.0 |
latest source/ R- | MetaHunt_0.1.0.tar.gz |
448.1 KiB |
0.1.0 |
2026-04-23 source/ R- | MetaHunt_0.1.0.tar.gz |
0 B |