Package: BSGW
Type: Package
Title: Bayesian Survival Model with Lasso Shrinkage Using Generalized
        Weibull Regression
Version: 0.9.4
Date: 2022-12-12
Author: Alireza S. Mahani, Mansour T.A. Sharabiani
Maintainer: Alireza S. Mahani <alireza.s.mahani@gmail.com>
Description: Bayesian survival model using Weibull regression on both
        scale and shape parameters. Dependence of shape parameter on
        covariates permits deviation from proportional-hazard
        assumption, leading to dynamic - i.e. non-constant with time -
        hazard ratios between subjects. Bayesian Lasso shrinkage in the
        form of two Laplace priors - one for scale and one for shape
        coefficients - allows for many covariates to be included.
        Cross-validation helper functions can be used to tune the
        shrinkage parameters. Monte Carlo Markov Chain (MCMC) sampling
        using a Gibbs wrapper around Radford Neal's univariate slice
        sampler (R package MfUSampler) is used for coefficient
        estimation.
License: GPL (>= 2)
Imports: foreach, doParallel, survival, MfUSampler, methods
NeedsCompilation: no
Packaged: 2026-07-02 08:38:19 UTC; root
Repository: https://asmahani.r-universe.dev
Date/Publication: 2022-12-12 12:10:08 UTC
RemoteUrl: https://github.com/cran/BSGW
RemoteRef: HEAD
RemoteSha: d130541a3f129bad54c20716e63448cfb37e6faa