Hierarchical Shrinkage Stan Models for Biomarker Selection

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) ). It implements the horseshoe and regularized horseshoe priors (Piironen and Vehtari (2017) ), as well as the projection predictive selection approach to recover a sparse set of predictive biomarkers (Piironen, Paasiniemi and Vehtari (2020) ).


Reference manual

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0.8.1 by Marco Colombo, 2 months ago


Report a bug at https://github.com/mcol/hsstan/issues

Browse source code at https://github.com/cran/hsstan

Authors: Marco Colombo [aut, cre] , Paul McKeigue [aut] , Athina Spiliopoulou [ctb]

Documentation:   PDF Manual  

GPL-3 license

Imports ggplot2, loo, parallel, pROC, Rcpp, RcppParallel, methods, rstan, rstantools, stats, utils

Suggests testthat

Linking to BH, Rcpp, RcppEigen, RcppParallel, StanHeaders, rstan

System requirements: GNU make

See at CRAN