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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 |
| Reference manual: | BayesReversePLLH.pdf |
| 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 |
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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.