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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.
| Version: | 1.0.0 |
| Imports: | pracma, selectiveInference, MASS |
| Published: | 2025-10-08 |
| DOI: | 10.32614/CRAN.package.VBMS (may not be active yet) |
| Author: | Lu Luo [aut, cre], Huiqiong Li [aut] |
| Maintainer: | Lu Luo <luolu at stu.ynu.edu.cn> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| CRAN checks: | VBMS results |
| Reference manual: | VBMS.html , VBMS.pdf |
| Package source: | VBMS_1.0.0.tar.gz |
| Windows binaries: | r-devel: VBMS_1.0.0.zip, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): VBMS_1.0.0.tgz, r-oldrel (arm64): VBMS_1.0.0.tgz, r-release (x86_64): VBMS_1.0.0.tgz, r-oldrel (x86_64): VBMS_1.0.0.tgz |
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