Package: SemiPar.depCens 0.1.3

SemiPar.depCens: Copula Based Cox Proportional Hazards Models for Dependent Censoring

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>.

Authors:Negera Wakgari Deresa [aut, cre], Ingrid Van Keilegom [aut]

SemiPar.depCens_0.1.3.tar.gz
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SemiPar.depCens_0.1.3.tgz(r-4.6-any)SemiPar.depCens_0.1.3.tgz(r-4.5-any)
SemiPar.depCens_0.1.3.tar.gz(r-4.7-any)SemiPar.depCens_0.1.3.tar.gz(r-4.6-any)
SemiPar.depCens_0.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
SemiPar.depCens/json (API)
NEWS

# Install 'SemiPar.depCens' in R:
install.packages('SemiPar.depCens', repos = c('https://nago2020.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/nago2020/semipar.depcens/issues

Datasets:
  • follic - Follicular Cell Lymphoma

On CRAN:

Conda:

3.78 score 3 stars 4 scripts 193 downloads 4 mentions 4 exports 18 dependencies

Last updated from:9a3b3d0070. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK178
source / vignettesOK164
linux-release-x86_64OK190
macos-release-arm64OK184
macos-oldrel-arm64OK170
windows-develOK244
windows-releaseOK191
windows-oldrelOK182
wasm-releaseOK105

Exports:fitDepCensfitIndepCensSolveLSolveLI

Dependencies:ADGofTestclustercodetoolscolorspacecopuladoParallelforeachgsliteratorslatticeMatrixmvtnormnumDerivpbivnormpcaPPpsplinestabledistsurvival