cevcmm
Communication-Efficient Varying Coefficient Mixed-Effects Models
Scalable inference for Varying Coefficient Mixed-Effects Models (VCMMs) with large, correlated random effects. Implements sufficient-statistics, one-step communication-efficient surrogate likelihood, and SVD-stabilized (Singular Value Decomposition) estimators with Kronecker and separable covariance structures. Implements the methodology of Jalili and Lin (2025) <doi:10.48550/arXiv.2511.12732>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.3 |
rolling linux/jammy R-4.5 | cevcmm_0.1.3.tar.gz |
489.7 KiB |
0.1.3 |
rolling linux/noble R-4.5 | cevcmm_0.1.3.tar.gz |
493.3 KiB |
0.1.3 |
rolling source/ R- | cevcmm_0.1.3.tar.gz |
289.1 KiB |
0.1.3 |
latest linux/jammy R-4.5 | cevcmm_0.1.3.tar.gz |
489.7 KiB |
0.1.3 |
latest linux/noble R-4.5 | cevcmm_0.1.3.tar.gz |
493.3 KiB |
0.1.3 |
latest source/ R- | cevcmm_0.1.3.tar.gz |
289.1 KiB |
0.1.3 |
2026-04-23 source/ R- | cevcmm_0.1.3.tar.gz |
0 B |