BayesReversePLLH: Fits the Bayesian Piecewise Linear Log-Hazard Model

Contains posterior samplers for the Bayesian piecewise linear log-hazard and piecewise exponential hazard models, including Cox models. Posterior mean restricted survival times are also computed for non-Cox an Cox models with only treatment indicators. The ApproxMean() function can be used to estimate restricted posterior mean survival times given a vector of patient covariates in the Cox model. Functions included to return the posterior mean hazard and survival functions for the piecewise exponential and piecewise linear log-hazard models. Chapple, AG, Peak, T, Hemal, A (2020). Under Revision.

Version: 1.5
Imports: Rcpp (≥ 0.12.18)
LinkingTo: Rcpp, RcppArmadillo
Published: 2022-10-20
DOI: 10.32614/CRAN.package.BayesReversePLLH
Author: Andrew G Chapple
Maintainer: Andrew G Chapple <achapp at>
License: GPL-2
NeedsCompilation: yes
CRAN checks: BayesReversePLLH results


Reference manual: BayesReversePLLH.pdf


Package source: BayesReversePLLH_1.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): BayesReversePLLH_1.5.tgz, r-oldrel (arm64): BayesReversePLLH_1.5.tgz, r-release (x86_64): BayesReversePLLH_1.5.tgz, r-oldrel (x86_64): BayesReversePLLH_1.5.tgz
Old sources: BayesReversePLLH archive


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