psbcGroup

swMATH24007CRANpsbcGroupMaRDI QIDQ35768

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

Kyu Ha Lee

Last update: 9 January 2024

Copyright license: GNU General Public License, version 3.0, GNU General Public License, version 2.0

Software version identifier: 1.5, 1.0, 1.1, 1.2, 1.3, 1.4, 1.7

Source code repository: https://github.com/cran/psbcGroup

Description

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>).

Cites work

• Bayesian Variable Selection in Semiparametric Proportional Hazards Model for High Dimensional Survival Data
• Survival prediction and variable selection with simultaneous shrinkage and grouping priors
• Variable selection for high-dimensional genomic data with censored outcomes using group lasso prior

Described by source

• Variable selection for high-dimensional genomic data with censored outcomes using group Lasso prior

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