Tests Controlling the FDR / FWER under Certain Copula Models (MHTcop)
Implements tests controlling the false discovery rate (FDR) / family-wise error rate (FWER) for some copula models.

Penalized Precision Matrix Estimation via ADMM (ADMMsigma)
Estimates a penalized precision matrix via the alternating direction method of multipliers (ADMM) algorithm. It currently supports a general elastic-net penalty that allows for both ridge and lasso-type penalties as special cases. This package is an alternative to the ‘glasso’ package. See Boyd et al (2010) <doi:10.1561/2200000016> for details regarding the estimation method.

Inverse Gamma-Gamma (IGG)
Implements Bayesian linear regression, normal means estimation, and variable selection using the inverse gamma-gamma prior, as introduced by Bai and Ghosh (2018) <arXiv:1710.04369>.

Multiple Imputation Random Lasso for Variable Selection with Missing Entries (MIRL)
Implements a variable selection and prediction method for high-dimensional data with missing entries following the paper Liu et al. (2016) <doi:10.1214/15-AOAS899>. It deals with missingness by multiple imputation and produces a selection probability for each variable following stability selection. The user can further choose a threshold for the selection probability to select a final set of variables. The threshold can be picked by cross validation or the user can define a practical threshold for selection probability. If you find this work useful for your application, please cite the method paper.

Group Sequential Designs with Negative Binomial Outcomes (gscounts)
Design and analysis of group sequential designs with negative binomial outcomes, as described by T Muetze, E Glimm, H Schmidli, T Friede (2017) <arXiv:1707.04612>.