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: 1.3
Imports: Rcpp (≥ 0.12.18)
LinkingTo: Rcpp, RcppArmadillo
Published: 2020-02-07
Author: Andrew G Chapple
Maintainer: Andrew G Chapple <achapp at lsuhsc.edu>
License: GPL-2
NeedsCompilation: yes
CRAN checks: BayesReversePLLH results

Downloads:

Reference manual: BayesReversePLLH.pdf
Package source: BayesReversePLLH_1.3.tar.gz
Windows binaries: r-devel: BayesReversePLLH_1.3.zip, r-devel-gcc8: BayesReversePLLH_1.3.zip, r-release: BayesReversePLLH_1.3.zip, r-oldrel: BayesReversePLLH_1.3.zip
OS X binaries: r-release: BayesReversePLLH_1.3.tgz, r-oldrel: BayesReversePLLH_1.3.tgz
Old sources: BayesReversePLLH archive

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