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BMIselect

1.0.10Package record

Bayesian MI-LASSO for Variable Selection on Multiply-Imputed Datasets

0packages depend
5.5Kdownloads / year
25.9%test coverage
13/13flavors OK

Overview

About

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 MI-LASSO function.

Install

Health

CRAN checks
13OK
Slowest check: 7.0 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-10-07
  • ERROR12 OK, 1 ERROR2026-07-10
  • OK13 OK2026-06-09
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK13 OK2026-05-02
Show 3 earlier changesHide 3 earlier changes
  • ERROR11 OK, 1 ERROR2026-04-25
  • OK14 OK2026-03-30
  • ERROR13 OK, 1 ERROR2026-03-10
Advisories

none known

Documentation

In release 1.0.10
READMENoVignettesYes · 1 · dynamicNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
13 (8 internal)includes a package overview page
Examples that run
100%5 run in a plain check
Exported functions with examples
100%
Documented parameters
97%
Return-value docs
100%
Help pages citing references
0%

Downloads

5.5K
CRAN downloads in the past year
Rank #8,541 · ~15/day · ~462/mo
Daily download trend is not available in this view yet.
37930 days
1.1K90 days
5.5K1 year
Compare downloads with other packages →
Also on139 r2u41 autocran

Dependencies

Declared dependencies
15 external dependencies (excludes base and recommended)

Installing BMIselect adds 67 packages (38 with compiled code, 46 MB of source tarballs). Heaviest: stringi 11 MB, lme4 4.3 MB, glmnet 2.7 MB.

Depends (1)
R >= 3.5.0
LinkingTo (2)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (3)
Author, Maintainer since 1.0.1 (2025)
Releases (6)

Pick two releases to compare their code metrics.

  • 1.0.10Latest
    record
    2026-10-07 · current release · diff ↗
  • 1.0.9
    record
    2026-08-21 · diff ↗ ·
    removed 6 exports
    ARD_mcmc, horseshoe_mcmc, multi_laplace_mcmc, projection_mean, projection_posterior, spike_laplace_partially_mcmc
  • 1.0.4
    record
    2026-07-09 · diff ↗
  • R
    R 4.6.0 released · 2026-04-24
  • 1.0.3
    record
    2025-08-25 · diff ↗
  • 1.0.2
    record
    2025-08-20 · diff ↗
  • 1.0.1
    record
    2025-07-09
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2025-07-09
Total releases
6 / 1 yrs
License
Apache License (>= 2)
Minimum R
≥ 3.5.0
Download size
70 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("BMIselect")
Zou, J., Chen, Q., & Wang, S. (2026). BMIselect: Bayesian MI-LASSO for Variable Selection on Multiply-Imputed Datasets (Version 1.0.10) [Computer software]. https://doi.org/10.32614/CRAN.package.BMIselect

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for BMIselect version 1.0.10 [Data set]. HJJB, LLC. Data release v2026-10-23. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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