My research group develops open-source software. Our software is publicly available on CRAN and GitHub.

  • SSGL: Spike-and-slab group lasso (SSGL) for group-regularized generalized linear models (GLMs) [Paper 1, Paper 2]

  • PGQR: Penalized generative quantile regression (PGQR), a deep learning generative approach for joint quantile regression [Paper]

  • MBSP: Gaussian multivariate Bayesian linear regression with shrinkage priors (MBSP) using the three parameter beta normal family [Paper]

  • NVCSSL: Nonparametric varying coefficient spike-and-slab lasso (NVC-SSL) for high-dimensional Bayesian varying coefficient models [Paper]

  • GBnpmle: Generative bootstrapping for nonparametric maximum likelihood estimation of a mixing density in latent variable models [Paper]

  • LMM-PROBE: Sparse high-dimensional linear mixed modeling based on a partitioned empirical Bayes ECM algorithm [Paper]

  • GUD: Bayesian modal regression based on the generalized unimodal distribution (GUD) family [Paper]

  • RobustBayesianCopas: Robust Bayesian Copas selection model for sensitivity analysis and quantifying the impact of publication bias [Paper]

  • MtMBSP: Mixed-type multivariate Bayesian regression with shrinkage priors (Mt-MBSP) using the three parameter beta normal family [Paper]

  • NormalBetaPrime: Bayesian univariate linear regression and sparse normal means estimation with the normal-beta prime prior [Paper 1, Paper 2]

  • ABSORB: A Bayesian Selection model for correcting Outcome Reporting Bias (ABSORB) in multivariate meta-analysis [Paper]