CRAN/E | survstan

survstan

Fitting Survival Regression Models via 'Stan'

Installation

About

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) ; 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.

github.com/fndemarqui/survstan
fndemarqui.github.io/survstan/
System requirements GNU make
Bug report File report

Key Metrics

Version 0.0.7.1
R ≥ 3.4.0
Published 2024-04-12 20 days ago
Needs compilation? yes
License MIT
License File
CRAN checks survstan results

Downloads

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Maintainer

Maintainer

Fabio Demarqui

fndemarqui@est.ufmg.br

Authors

Fabio Demarqui

aut / cre / cph

Andrew Johnson

ctb

Material

README
NEWS
Reference manual
Package source

Vignettes

Likelihood ratio tests with the survstan package
Introduction to the R package survstan

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

survstan archive

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

Suggests

emmeans ≥ 1.4.2
estimability
GGally
knitr
rmarkdown
testthat ≥ 3.0.0

LinkingTo

BH ≥ 1.66.0
Rcpp ≥ 0.12.0
RcppEigen ≥ 0.3.3.3.0
RcppParallel ≥ 5.0.1
rstan ≥ 2.26.0
StanHeaders ≥2.26.0