An R package BSGS is provided for the integration of Bayesian variable and sparse group selection separately proposed by Chen et al. (2011) and Chen et al. (in press) for variable selection problems, even in the cases of large p and small n. This package is designed for variable selection problems including the identification of the important groups of variables and the active variables within the important groups. This article introduces the functions in the BSGS package that can be used to perform sparse group selection as well as variable selection through simulation studies and real data.
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For attribution, please cite this work as
Lee & Chen, "BSGS: Bayesian Sparse Group Selection", The R Journal, 2015
BibTeX citation
@article{RJ-2015-025,
author = {Lee, Kuo-Jung and Chen, Ray-Bing},
title = {BSGS: Bayesian Sparse Group Selection},
journal = {The R Journal},
year = {2015},
note = {https://doi.org/10.32614/RJ-2015-025},
doi = {10.32614/RJ-2015-025},
volume = {7},
issue = {2},
issn = {2073-4859},
pages = {122-133}
}