print.hsstan

Print a summary for the fitted model

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>).

Marco Colombo

hsstan

Hierarchical Shrinkage Stan Models for Biomarker Selection

Paul McKeigue

Athina Spiliopoulou

print.hsstan function

<dl><dt>x</dt>
<dd>An object of class <code>hsstan</code>.</dd>
<dt>...</dt>
<dd>Further arguments to <code><a href="/link/summary()?package=hsstan&version=0.8.2" data-mini-rdoc="hsstan::summary()">summary()</a></code>.</dd></dl>

Arguments

Print a summary for the fitted model — print.hsstan

<dl>

<dt>x</dt>
<dd>An object of class <code>hsstan</code>.</dd>


<dt>...</dt>
<dd>Further arguments to <code><a href='https://rdrr.io/r/base/summary.html'>summary()</a></code>.</dd>

</dl>

print.hsstan: Print a summary for the fitted model

Description

Usage

Arguments