cevcmm-package: cevcmm: Communication-Efficient Varying Coefficient...

cevcmm-packageR Documentation

cevcmm: Communication-Efficient Varying Coefficient Mixed-Effects Models

Description

Scalable inference for Varying Coefficient Mixed-Effects Models (VCMMs) with large, correlated random effects. The package implements:

Details

  • Sufficient-statistics (SS) iterative estimator (Algorithm 1).

  • One-step communication-efficient surrogate likelihood (CSL) estimator.

  • SVD-stabilized variants for ill-conditioned random-effect Gram matrices.

  • Kronecker and separable covariance structures for origin-destination and group-shared random effects.

The package is in early development. See the project ROADMAP for the current status.

Author(s)

Maintainer: Lida Jalili lchalangarjalilideh1@gsu.edu

Authors:

References

Jalili, L. and Lin, L.-H. (2025). Scalable and Communication-Efficient Varying Coefficient Mixed Effect Models: Methodology, Theory, and Applications.

See Also

Useful links:


cevcmm documentation built on July 24, 2026, 5:07 p.m.