rsurv: Random Generation of Survival Data
Random generation of survival data from a wide range of regression models, including accelerated failure time (AFT), proportional hazards (PH), proportional odds (PO), accelerated hazard (AH), Yang and Prentice (YP), and extended hazard (EH) models. The package 'rsurv' also stands out by its ability to generate survival data from an unlimited number of baseline distributions provided that an implementation of the quantile function of the chosen baseline distribution is available in R. Another nice feature of the package 'rsurv' lies in the fact that linear predictors are specified via a formula-based approach, facilitating the inclusion of categorical variables and interaction terms. The functions implemented in the package 'rsurv' can also be employed to simulate survival data with more complex structures, such as survival data with different types of censoring mechanisms, survival data with cure fraction, survival data with random effects (frailties), multivariate survival data, and competing risks survival data. Details about the R package 'rsurv' can be found in Demarqui (2024) <doi:10.48550/arXiv.2406.01750>.
| Version: |
0.0.1 |
| Depends: |
dplyr, R (≥ 3.4.0) |
| Imports: |
Rdpack, stabledist |
| Suggests: |
copula, flexsurv, frailtyEM, GGally, knitr, LambertW, rmarkdown, survival, survstan, testthat (≥ 3.0.0) |
| Published: |
2024-06-06 |
| DOI: |
10.32614/CRAN.package.rsurv |
| Author: |
Fabio Demarqui 
[aut, cre, cph] |
| Maintainer: |
Fabio Demarqui <fndemarqui at est.ufmg.br> |
| BugReports: |
https://github.com/fndemarqui/rsurv/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://github.com/fndemarqui/rsurv,
https://fndemarqui.github.io/rsurv/ |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
rsurv results |
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