Variational Bayesian Algorithm for Multi-Source Heterogeneous Models R package VBMS version 1.0.0 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. Software Imports: pracma, selectiveInference, MASS Lu Luo <luolu@stu.ynu.edu.cn> Comprehensive R Archive Network (CRAN) Lu Luo [aut, cre], Huiqiong Li [aut] MIT + file LICENSE (https://CRAN.R-project.org/package=VBMS/LICENSE) 2025-10-08 application/tgz https://CRAN.R-project.org/package=VBMS doi:10.32614/CRAN.package.VBMS