Crandore Hub

VBMS

Variational Bayesian Algorithm for Multi-Source Heterogeneous Models

A Variational Bayesian algorithm for high-dimensional multi-source heterogeneous linear models. More details have been written up in a paper submitted to the journal Statistics in Medicine, and the details of variational Bayesian methods can be found in Ray and Szabo (2021) <doi:10.1080/01621459.2020.1847121>. It simultaneously performs parameter estimation and variable selection. The algorithm supports two model settings: (1) local models, where variable selection is only applied to homogeneous coefficients, and (2) global models, where variable selection is also performed on heterogeneous coefficients. Two forms of Spike-and-Slab priors are available: the Laplace distribution and the Gaussian distribution as the Slab component.

Versions across snapshots

VersionRepositoryFileSize
1.0.0 rolling linux/jammy R-4.5 VBMS_1.0.0.tar.gz 48.5 KiB
1.0.0 rolling linux/noble R-4.5 VBMS_1.0.0.tar.gz 48.3 KiB
1.0.0 rolling source/ R- VBMS_1.0.0.tar.gz 6.0 KiB
1.0.0 latest linux/jammy R-4.5 VBMS_1.0.0.tar.gz 48.5 KiB
1.0.0 latest linux/noble R-4.5 VBMS_1.0.0.tar.gz 48.3 KiB
1.0.0 latest source/ R- VBMS_1.0.0.tar.gz 6.0 KiB
1.0.0 2026-04-26 source/ R- VBMS_1.0.0.tar.gz 6.0 KiB
1.0.0 2026-04-23 source/ R- VBMS_1.0.0.tar.gz 6.0 KiB
1.0.0 2026-04-09 windows/windows R-4.5 VBMS_1.0.0.zip 50.8 KiB

Dependencies (latest)

Imports