Provides a suite of Bayesian MI-LASSO for variable selection methods for multiply-imputed datasets. The package includes four Bayesian MI-LASSO models using shrinkage (Multi-Laplace, Horseshoe, ARD) and Spike-and-Slab (Spike-and-Laplace) priors, along with tools for model fitting via MCMC, four-step projection predictive variable selection, and hyperparameter calibration. Methods are suitable for both continuous and binary covariates under missing-at-random or missing-completely-at-random assumptions. See Zou, J., Wang, S. and Chen, Q. (2025), Bayesian MI-LASSO for Variable Selection on Multiply-Imputed Data. ArXiv, 2211.00114. <doi:10.48550/arXiv.2211.00114> for more details. We also provide the frequentist's MI-LASSO function.
| Version: | 1.0.3 |
| Depends: | R (≥ 3.5.0) |
| Imports: | MCMCpack, mvnfast, GIGrvg, MASS, Rfast, foreach, doParallel, arm, mice, abind, stringr, stats, posterior |
| Suggests: | testthat, knitr, rmarkdown |
| Published: | 2025-08-25 |
| DOI: | 10.32614/CRAN.package.BMIselect |
| Author: | Jungang Zou [aut, cre], Sijian Wang [aut], Qixuan Chen [aut] |
| Maintainer: | Jungang Zou <jungang.zou at gmail.com> |
| License: | Apache License (≥ 2) |
| NeedsCompilation: | no |
| CRAN checks: | BMIselect results |
| Reference manual: | BMIselect.html , BMIselect.pdf |
| Vignettes: |
An Introduction to BMIselect (source, R code) |
| Package source: | BMIselect_1.0.3.tar.gz |
| Windows binaries: | r-devel: BMIselect_1.0.3.zip, r-release: BMIselect_1.0.3.zip, r-oldrel: BMIselect_1.0.3.zip |
| macOS binaries: | r-release (arm64): BMIselect_1.0.3.tgz, r-oldrel (arm64): BMIselect_1.0.3.tgz, r-release (x86_64): BMIselect_1.0.3.tgz, r-oldrel (x86_64): BMIselect_1.0.3.tgz |
| Old sources: | BMIselect archive |
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