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:	1.4
Imports:	Rcpp (≥ 0.12.18)
LinkingTo:	Rcpp, RcppArmadillo
Published:	2020-10-06
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_1.4.tar.gz
Windows binaries:	r-devel: BayesReversePLLH_1.4.zip, r-release: BayesReversePLLH_1.4.zip, r-oldrel: BayesReversePLLH_1.4.zip
macOS binaries:	r-release (arm64): BayesReversePLLH_1.4.tgz, r-oldrel (arm64): BayesReversePLLH_1.4.tgz, r-release (x86_64): BayesReversePLLH_1.4.tgz, r-oldrel (x86_64): BayesReversePLLH_1.4.tgz
Old sources:	BayesReversePLLH archive

Linking:

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