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>.
