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invGauss: Threshold Regression that Fits the (Randomized Drift) Inverse Gaussian Distribution to Survival Data

Fits the (randomized drift) inverse Gaussian distribution to survival data. The model is described in Aalen OO, Borgan O, Gjessing HK. Survival and Event History Analysis. A Process Point of View. Springer, 2008. It is based on describing time to event as the barrier hitting time of a Wiener process, where drift towards the barrier has been randomized with a Gaussian distribution. The model allows covariates to influence starting values of the Wiener process and/or average drift towards a barrier, with a user-defined choice of link functions.

Version: 1.2
Depends: survival
Imports: optimx
Published: 2022-05-20
DOI: 10.32614/CRAN.package.invGauss
Author: Hakon K. Gjessing
Maintainer: Hakon K. Gjessing <hakon.gjessing at uib.no>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www.uib.no/smis/gjessing/projects/invgauss/
NeedsCompilation: no
In views: Survival
CRAN checks: invGauss results

Documentation:

Reference manual: invGauss.pdf

Downloads:

Package source: invGauss_1.2.tar.gz
Windows binaries: r-devel: invGauss_1.2.zip, r-release: invGauss_1.2.zip, r-oldrel: invGauss_1.2.zip
macOS binaries: r-release (arm64): invGauss_1.2.tgz, r-oldrel (arm64): invGauss_1.2.tgz, r-release (x86_64): invGauss_1.2.tgz, r-oldrel (x86_64): invGauss_1.2.tgz
Old sources: invGauss archive

Reverse dependencies:

Reverse imports: ahMLE
Reverse suggests: multipleOutcomes

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.