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)
).