The <code>VS</code> is a function to perform variable selection using SNC-BIC thresholding method

Algorithms to implement various Bayesian penalized survival regression models including: semiparametric proportional hazards models with lasso priors (Lee et al., Int J Biostat, 2011 <doi:10.2202/1557-4679.1301>) and three other shrinkage and group priors (Lee et al., Stat Anal Data Min, 2015 <doi:10.1002/sam.11266>); parametric accelerated failure time models with group/ordinary lasso prior (Lee et al. Comput Stat Data Anal, 2017 <doi:10.1016/j.csda.2017.02.014>).

Kyu Lee

psbcGroup

Penalized Parametric and Semiparametric Bayesian Survival Models
with Shrinkage and Grouping Priors

VS function

<dl> <dt>fit</dt>
<dd>an object of class <code>aftGL</code>, <code>psbcEN</code>, <code>psbcFL</code>, or <code>psbcGL</code>.</dd> <dt>X</dt>
<dd>a covariate matrix, <code>n</code> observations by <code>p</code> variables </dd> <dt>psiVec</dt>
<dd>a vector of candidate threshold values for the SNC step</dd></dl>

Arguments

Author

Function to perform variable selection using SNC-BIC thresholding method — VS

<dl>

 <dt>fit</dt>
<dd>an object of class <code>aftGL</code>, <code>psbcEN</code>, <code>psbcFL</code>, or <code>psbcGL</code>.</dd>

 <dt>X</dt>
<dd>a covariate matrix, <code>n</code> observations by <code>p</code> variables </dd>

 <dt>psiVec</dt>
<dd>a vector of candidate threshold values for the SNC step</dd>

</dl>

VS: Function to perform variable selection using SNC-BIC thresholding method

Description

Usage

Arguments

Author

References

See Also