Threshold Regression that Fits the (Randomized Drift) Inverse Gaussian Distribution to Survival Data
Overview
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.
Install
Health
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Hakon K. Gjessing <hakon.gjessing@uib.no>’
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Authors@R: person(given = c("Hakon", "K."),
family = "Gjessing",
role = c("aut", "cre"),
email = "hakon.gjessing@uib.no")
as necessary.- NOTE11 OK, 2 NOTENow
- NOTE12 OK, 2 NOTE2026-03-10
Documentation
- Help pages
- 3
- Examples that run
- 100%2 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 93%
- Return-value docs
- 100%
- Help pages citing references
- 100%
Downloads
Dependencies
Installing invGauss adds 4 packages (1 with compiled code, 4.8 MB of source tarballs). Heaviest: optimx 2.2 MB, nloptr 2.1 MB, pracma 389 KB.
Code & Tests
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- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 1.2Latest
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- RR 3.4.0 released · 2017-04-21
- RR 3.3.0 released · 2016-05-03
- RR 3.2.0 released · 2015-04-16
- RR 3.1.0 released · 2014-04-10
- 1.12014-03-28
- RR 3.0.0 released · 2013-04-03
Package metadata
- First published
- 2014-03-28
- Total releases
- 2 / 12 yrs
- License
- GPL (>= 2) OSI
- Bundled data
- 2.9 KB / 1 file
- Download size
- 15 KB
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