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cpsurvsim: Simulating Survival Data from Change-Point Hazard Distributions

Simulates time-to-event data with type I right censoring using two methods: the inverse CDF method and our proposed memoryless method. The latter method takes advantage of the memoryless property of survival and simulates a separate distribution between change-points. We include two parametric distributions: exponential and Weibull. Inverse CDF method draws on the work of Rainer Walke (2010), <https://www.demogr.mpg.de/papers/technicalreports/tr-2010-003.pdf>.

Version: 1.2.2
Depends: R (≥ 3.6.0)
Imports: plyr (≥ 1.8.5), stats, Hmisc (≥ 4.3.0), knitr (≥ 1.27)
Suggests: rmarkdown, testthat
Published: 2023-09-05
DOI: 10.32614/CRAN.package.cpsurvsim
Author: Camille Hochheimer [aut, cre]
Maintainer: Camille Hochheimer <dochoch19 at gmail.com>
BugReports: https://github.com/camillejo/cpsurvsim/issues
License: GPL (≥ 3)
URL: https://github.com/camillejo/cpsurvsim
NeedsCompilation: no
Citation: cpsurvsim citation info
CRAN checks: cpsurvsim results

Documentation:

Reference manual: cpsurvsim.pdf
Vignettes: Introduction to cpsurvsim

Downloads:

Package source: cpsurvsim_1.2.2.tar.gz
Windows binaries: r-devel: cpsurvsim_1.2.2.zip, r-release: cpsurvsim_1.2.2.zip, r-oldrel: cpsurvsim_1.2.2.zip
macOS binaries: r-release (arm64): cpsurvsim_1.2.2.tgz, r-oldrel (arm64): cpsurvsim_1.2.2.tgz, r-release (x86_64): cpsurvsim_1.2.2.tgz, r-oldrel (x86_64): cpsurvsim_1.2.2.tgz
Old sources: cpsurvsim archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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