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>.
Version: 0.0.7.1 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 (≥ 0.3.3.3.0), 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 [aut, cre, cph], Andrew Johnson [ctb] Maintainer: Fabio Demarqui <fndemarqui at est.ufmg.br> BugReports: https://github.com/fndemarqui/survstan/issues License: MIT + file LICENSE URL: https://github.com/fndemarqui/survstan, https://fndemarqui.github.io/survstan/ NeedsCompilation: yes SystemRequirements: GNU make Materials: README NEWS In views: Survival CRAN checks: survstan results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=survstan to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4