Hierarchical Shrinkage Stan Models for Biomarker Selection R package hsstan version 0.8.2 CRAN Task View: Omics (https://CRAN.R-project.org/view=Omics) Linear and logistic regression models penalized with hierarchical shrinkage priors for selection of biomarkers (or more general variable selection), which can be fitted using Stan (Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>). It implements the horseshoe and regularized horseshoe priors (Piironen and Vehtari (2017) <doi:10.1214/17-EJS1337SI>), as well as the projection predictive selection approach to recover a sparse set of predictive biomarkers (Piironen, Paasiniemi and Vehtari (2020) <doi:10.1214/20-EJS1711>). Software Depends: R (>= 3.6) Imports: ggplot2, loo (>= 2.1.0), parallel, pROC, Rcpp, methods, rstan (>= 2.26.0), rstantools (>= 2.0.0), stats, utils LinkingTo: BH (>= 1.66.0.1), Rcpp (>= 0.12.15), RcppEigen (>= 0.3.3.4.0), RcppParallel (>= 5.0.1), StanHeaders (>= 2.26.0), rstan (>= 2.26.0) Suggests: testthat (>= 2.1.0) Marco Colombo <mar.colombo13@gmail.com> Comprehensive R Archive Network (CRAN) Marco Colombo [aut, cre] (ORCID: <https://orcid.org/0000-0001-6672-0623>), Paul McKeigue [aut] (ORCID: <https://orcid.org/0000-0002-5217-1034>), Athina Spiliopoulou [ctb] (ORCID: <https://orcid.org/0000-0002-5929-6585>) GPL-3 2024-01-13 application/tgz https://CRAN.R-project.org/package=hsstan doi:10.32614/CRAN.package.hsstan