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Copula based Cox proportional hazards models for survival data subject to dependent censoring. This approach does not assume that the parameter defining the copula is known. The dependency parameter is estimated with other finite model parameters by maximizing a Pseudo likelihood function. The cumulative hazard function is estimated via estimating equations derived based on martingale ideas. Available copula functions include Frank, Gumbel and Normal copulas. Only Weibull and lognormal models are allowed for the censoring model, even though any parametric model that satisfies certain identifiability conditions could be used. Implemented methods are described in the article "Copula based Cox proportional hazards models for dependent censoring" by Deresa and Van Keilegom (2024) <doi:10.1080/01621459.2022.2161387>.
Version: | 0.1.3 |
Depends: | R (≥ 3.5.0) |
Imports: | survival, copula, stats, foreach, parallel, doParallel, pbivnorm |
Suggests: | testthat (≥ 3.0.0) |
Published: | 2024-08-26 |
DOI: | 10.32614/CRAN.package.SemiPar.depCens |
Author: | Negera Wakgari Deresa [aut, cre], Ingrid Van Keilegom [aut] |
Maintainer: | Negera Wakgari Deresa <negera.deresa at gmail.com> |
BugReports: | https://github.com/Nago2020/SemiPar.depCens/issues |
License: | GPL-3 |
URL: | https://github.com/Nago2020/SemiPar.depCens |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | SemiPar.depCens results |
Reference manual: | SemiPar.depCens.pdf |
Package source: | SemiPar.depCens_0.1.3.tar.gz |
Windows binaries: | r-devel: SemiPar.depCens_0.1.3.zip, r-release: SemiPar.depCens_0.1.3.zip, r-oldrel: SemiPar.depCens_0.1.3.zip |
macOS binaries: | r-release (arm64): SemiPar.depCens_0.1.3.tgz, r-oldrel (arm64): SemiPar.depCens_0.1.3.tgz, r-release (x86_64): SemiPar.depCens_0.1.3.tgz, r-oldrel (x86_64): SemiPar.depCens_0.1.3.tgz |
Old sources: | SemiPar.depCens archive |
Reverse imports: | depCensoring |
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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.