survstan: Fitting Survival Regression Models via 'Stan'

Parametric survival regression models under the maximum likelihood approach via 'Stan'. Implemented regression models include accelerated failure time models, proportional hazards models, proportional odds models, accelerated hazard models, Yang and Prentice models, and extended hazard models. Available baseline survival distributions include exponential, Weibull, log-normal, log-logistic, gamma, generalized gamma, rayleigh, Gompertz and fatigue (Birnbaum-Saunders) distributions. References: Lawless (2002) <ISBN:9780471372158>; Bennett (1982) <doi:10.1002/sim.4780020223>; Chen and Wang(2000) <doi:10.1080/01621459.2000.10474236>; Demarqui and Mayrink (2021) <doi:10.1214/20-BJPS471>.

Depends: R (≥ 3.4.0), survival
Imports: actuar (≥ 3.0.0), broom, doFuture, dplyr, extraDistr, foreach, future, generics, ggplot2, gridExtra, MASS, methods, purrr, Rcpp (≥ 0.12.0), RcppParallel (≥ 5.0.1), Rdpack, rlang, rstan (≥ 2.26.0), rstantools (≥ 2.3.1), tibble, tidyr
LinkingTo: BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥, RcppParallel (≥ 5.0.1), rstan (≥ 2.26.0), StanHeaders (≥ 2.26.0)
Suggests: emmeans (≥ 1.4.2), estimability, GGally, knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-04-12
DOI: 10.32614/CRAN.package.survstan
Author: Fabio Demarqui ORCID iD [aut, cre, cph], Andrew Johnson [ctb]
Maintainer: Fabio Demarqui <fndemarqui at>
License: MIT + file LICENSE
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README NEWS
CRAN checks: survstan results


Reference manual: survstan.pdf
Vignettes: Likelihood ratio tests with the survstan package
Introduction to the R package survstan


Package source: survstan_0.0.7.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): survstan_0.0.7.1.tgz, r-oldrel (arm64): survstan_0.0.7.1.tgz, r-release (x86_64): survstan_0.0.7.1.tgz, r-oldrel (x86_64): survstan_0.0.7.1.tgz
Old sources: survstan archive

Reverse dependencies:

Reverse suggests: rsurv


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