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hsstan: 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) <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>).

Version: 0.8.2
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)
Published: 2024-01-13
DOI: 10.32614/CRAN.package.hsstan
Author: Marco Colombo ORCID iD [aut, cre], Paul McKeigue ORCID iD [aut], Athina Spiliopoulou ORCID iD [ctb]
Maintainer: Marco Colombo <mar.colombo13 at gmail.com>
BugReports: https://github.com/mcol/hsstan/issues
License: GPL-3
URL: https://github.com/mcol/hsstan
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README NEWS
In views: Omics
CRAN checks: hsstan results

Documentation:

Reference manual: hsstan.pdf

Downloads:

Package source: hsstan_0.8.2.tar.gz
Windows binaries: r-devel: hsstan_0.8.2.zip, r-release: hsstan_0.8.2.zip, r-oldrel: hsstan_0.8.2.zip
macOS binaries: r-release (arm64): hsstan_0.8.2.tgz, r-oldrel (arm64): hsstan_0.8.2.tgz, r-release (x86_64): hsstan_0.8.2.tgz, r-oldrel (x86_64): hsstan_0.8.2.tgz
Old sources: hsstan archive

Reverse dependencies:

Reverse suggests: nestedcv

Linking:

Please use the canonical form https://CRAN.R-project.org/package=hsstan to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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