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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 lsuhsc.edu>
License: GPL-2
NeedsCompilation: yes
CRAN checks: BayesReversePLLH results

Documentation:

Reference manual: BayesReversePLLH.pdf

Downloads:

Package source: BayesReversePLLH_1.5.tar.gz
Windows binaries: r-devel: BayesReversePLLH_1.5.zip, r-release: BayesReversePLLH_1.5.zip, r-oldrel: BayesReversePLLH_1.5.zip
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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=BayesReversePLLH to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.