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hsstan

Hierarchical Shrinkage Stan Models for Biomarker Selection

v0.8.2 · Jan 13, 2024 · GPL-3

Description

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>).

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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-oldrel-macos-arm64

installed package size

  installed size is 90.0Mb
  sub-directories of 1Mb or more:
    libs  89.5Mb
NOTE r-oldrel-macos-x86_64

installed package size

  installed size is 79.3Mb
  sub-directories of 1Mb or more:
    libs  78.8Mb

Reverse Dependencies (1)

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Dependency Network

Dependencies Reverse dependencies ggplot2 loo pROC Rcpp rstan rstantools nestedcv hsstan

Version History

new 0.8.2 Mar 9, 2026