Package: survobj 3.2.0

survobj: Simulate Parametric and Semi-Parametric Survival Times with Object-Oriented Design

Simulate parametric and semi-parametric survival times through a consistent, reusable interface for each distribution, using an object-oriented design. Supported distributions include Exponential, Weibull, Gompertz, Log-Logistic, Log-Normal, and Piecewise Exponential. Random variates can be generated under Proportional Hazards, Accelerated Failure Time, and Extended Hazards models, as well as under renewal and non-homogeneous Poisson recurrent event processes, following the methods described by Bender (2003) <doi:10.5282/UBM/EPUB.1716> and Leemis (1987) in Operations Research, 35(6), 892-894.

Authors:Aponte John [aut, cre, cph]

survobj_3.2.0.tar.gz
survobj_3.2.0.zip(r-4.7-any)survobj_3.2.0.zip(r-4.6-any)survobj_3.2.0.zip(r-4.5-any)
survobj_3.2.0.tgz(r-4.6-any)survobj_3.2.0.tgz(r-4.5-any)
survobj_3.2.0.tar.gz(r-4.7-any)survobj_3.2.0.tar.gz(r-4.6-any)
survobj_3.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
survobj/json (API)

# Install 'survobj' in R:
install.packages('survobj', repos = c('https://johnaponte.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/johnaponte/survobj/issues

Pkgdown/docs site:https://johnaponte.github.io

On CRAN:

Conda:

4.63 score 1 stars 17 scripts 315 downloads 34 exports 32 dependencies

Last updated from:bd6cc76618. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK196
source / vignettesOK261
linux-releaseOK199
macos-releaseOK135
macos-oldrelOK127
windows-develOK142
windows-releaseOK145
windows-oldrelOK132
wasm-releaseOK129

Exports:censor_eventcensor_timecompare_survivalCum_Hfxdtomdtoyggplot_survival_aftggplot_survival_ehggplot_survival_hrggplot_survival_randomhfxinvCum_Hfxis_single_numbermtodmtoynhppaftnhpphrplot_survivalrenewaftrenewhrrsurvrsurvaftrsurvehrsurvhrs_exponentials_factorys_gompertzs_loglogistics_lognormals_piecewises_weibullsfxytodytom

Dependencies:clicpp11dplyrfarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMatrixpillarpkgconfigpurrrR6RColorBrewerrlangS7scalesstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr

Defining and using objects of class SURVIVAL
Introduction | Exponential Distribution | Weibull distribution | Gompertz distribution | Piecewise Exponential distribution | Log-logistic distribution | Log-Normal distribution | Comparison of SURVIVAL objects | References
Rendered fromexample_distributions.Rmdusingknitr::rmarkdown

Last update: 2026-09-20
Started: 2023-11-29

Simulation of survival times
Introduction | Generation of Proportional Hazard times | Generation of Acceleration Failure Times | Generation of Extended Hazards times | Simulating recurrent episodes | Renewal process | Non-homogeneous Poisson process | References
Rendered fromsimulation_distributions.Rmdusingknitr::rmarkdown

Last update: 2026-09-20
Started: 2023-12-29

Simulating trials with multiple events
Introduction | Trial simulation | Analysis of the simulation | For recurrent events | For first or only event | References
Rendered fromsimulation_recurent.Rmdusingknitr::rmarkdown

Last update: 2026-09-20
Started: 2024-01-29

Simulating trials with survival endpoints
Introduction | Empirical power for superiority | Simulation | Analyze the simulation | Conclusion
Rendered fromsimulation_trials.Rmdusingknitr::rmarkdown

Last update: 2026-09-20
Started: 2023-11-29

Simulation trials: non-proportional hazard
Introduction | Empirical power to evaluate non-proportionality of the hazard | Simulation | Analyze the simulation | Conclusion | References
Rendered fromsimulation_trials2.Rmdusingknitr::rmarkdown

Last update: 2026-09-20
Started: 2023-11-30