**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>.

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