| mBvs-package {mBvs} | R Documentation |
Bayesian Variable Selection Methods for Multivariate Data
Description
Bayesian variable selection methods for data with multivariate responses and multiple covariates. The package contains implementations of multivariate Bayesian variable selection methods for continuous data and zero-inflated count data.
Details
The package includes the following function:
mvnBvs | Bayesian variable selection for data with multivariate continuous responses |
mzipBvs | Bayesian variable selection for conditional multivariate zero-inflated Poisson models |
mmzipBvs | Bayesian variable selection for marginalized multivariate zero-inflated Poisson models |
| Package: | mBvs |
| Type: | Package |
| Version: | 1.92 |
| Date: | 2024-4-13 |
| License: | GPL (>= 2) |
| LazyLoad: | yes |
Author(s)
Kyu Ha Lee, Mahlet G. Tadesse, Brent A. Coull, Jacqueline R. Starr
Maintainer: Kyu Ha Lee <klee15239@gmail.com>
References
Lee, K. H., Tadesse, M. G., Baccarelli, A. A., Schwartz J., and Coull, B. A. (2017),
Multivariate Bayesian variable selection exploiting dependence structure among outcomes:
application to air pollution effects on DNA methylation, Biometrics, Volume 73, Issue 1, pages 232-241.
Lee, K. H., Coull, B. A., Moscicki, A.-B., Paster, B. J., Starr, J. R. (2020),
Bayesian variable selection for multivariate zero-inflated models: application to microbiome count data, Biostatistics, Volume 21, Issue 3, Pages 499-517