Package: invGauss 1.2

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.

Authors:Hakon K. Gjessing

invGauss_1.2.tar.gz
invGauss_1.2.zip(r-4.5)invGauss_1.2.zip(r-4.4)invGauss_1.2.zip(r-4.3)
invGauss_1.2.tgz(r-4.5-any)invGauss_1.2.tgz(r-4.4-any)invGauss_1.2.tgz(r-4.3-any)
invGauss_1.2.tar.gz(r-4.5-noble)invGauss_1.2.tar.gz(r-4.4-noble)
invGauss_1.2.tgz(r-4.4-emscripten)invGauss_1.2.tgz(r-4.3-emscripten)
invGauss.pdf |invGauss.html✨
invGauss/json (API)

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

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.48 score 1 packages 5 scripts 255 downloads 1 exports 7 dependencies

Last updated 3 years agofrom:d45775d995. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 20 2025
R-4.5-winOKFeb 20 2025
R-4.5-macOKFeb 20 2025
R-4.5-linuxOKFeb 20 2025
R-4.4-winOKFeb 20 2025
R-4.4-macOKFeb 20 2025
R-4.3-winOKFeb 20 2025
R-4.3-macOKFeb 20 2025

Exports:invGauss

Dependencies:latticeMatrixnloptrnumDerivoptimxpracmasurvival