Package: BayesReversePLLH
Type: Package
Title: Fits the Bayesian Piecewise Linear Log-Hazard Model
Version: 1.5
Date: 2022-10-19
Author: Andrew G Chapple 
Maintainer: Andrew G Chapple <achapp@lsuhsc.edu>
Description: 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.
License: GPL-2
Encoding: UTF-8
Imports: Rcpp (>= 0.12.18)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2022-10-19 13:41:46 UTC; achapp
Repository: CRAN
Date/Publication: 2022-10-20 14:08:01 UTC
Built: R 4.1.2; x86_64-apple-darwin17.0; 2022-10-21 10:24:26 UTC; unix
Archs: BayesReversePLLH.so.dSYM
