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

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

## Documentation for package ‘BMIselect’ version 1.0.3

- DESCRIPTION file
- User guides, package vignettes and other documentation

## Help Pages

ARD_mcmc | ARD MCMC Sampler for Multiply-Imputed Regression
BMI_LASSO | Bayesian MI-LASSO for Multiply-Imputed Regression
horseshoe_mcmc | Horseshoe MCMC Sampler for Multiply-Imputed Regression
MI_LASSO | Multiple-Imputation LASSO (MI-LASSO)
multi_laplace_mcmc | Multi-Laplace MCMC Sampler for Multiply-Imputed Regression
projection_mean | Projecting Posterior Means of Full-Model Coefficients onto a Reduced Subset Model
projection_posterior | Projection of Full-Posterior Draws onto a Reduced-Subset Model
sim_A | Simulate dataset A: Independent continuous covariates with MCAR/MAR missingness
sim_B | Simulate dataset B: AR(1)-correlated continuous covariates with MCAR/MAR missingness
sim_C | Simulate dataset C: AR(1)-latent Gaussian dichotomized to binary covariates with MCAR/MAR missingness
spike_laplace_partially_mcmc | Spike-and-Laplace MCMC Sampler for Multiply-Imputed Regression