The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

Colossus: "Risk Model Regression and Analysis with Complex Non-Linear Models"

Performs survival analysis using general non-linear models. Risk models can be the sum or product of terms. Each term is the product of exponential/linear functions of covariates. Additionally sub-terms can be defined as a sum of exponential, linear threshold, and step functions. Cox Proportional hazards <https://en.wikipedia.org/wiki/Proportional_hazards_model>, Poisson <https://en.wikipedia.org/wiki/Poisson_regression>, and Fine-Grey competing risks <https://www.publichealth.columbia.edu/research/population-health-methods/competing-risk-analysis> regression are supported. This work was sponsored by NASA Grant 80NSSC19M0161 through a subcontract from the National Council on Radiation Protection and Measurements (NCRP). The computing for this project was performed on the Beocat Research Cluster at Kansas State University, which is funded in part by NSF grants CNS-1006860, EPS-1006860, EPS-0919443, ACI-1440548, CHE-1726332, and NIH P20GM113109.

Version: 1.1.4.2
Imports: Rcpp, data.table, parallel, stats, utils, rlang, callr, stringr, processx
LinkingTo: Rcpp, RcppEigen, testthat
Suggests: knitr, rmarkdown, testthat, xml2, ggplot2, pandoc, spelling, survival
Published: 2024-10-21
DOI: 10.32614/CRAN.package.Colossus
Author: Eric Giunta ORCID iD [aut, cre], Amir Bahadori ORCID iD [ctb], Dan Andresen [ctb], Linda Walsh ORCID iD [ctb], Benjamin French ORCID iD [ctb], Lawrence Dauer [ctb], John Boice Jr ORCID iD [ctb], Kansas State University [cph], NASA [fnd], NCRP [fnd], NRC [fnd]
Maintainer: Eric Giunta <egiunta at ksu.edu>
BugReports: https://github.com/ericgiunta/Colossus/issues
License: GPL (≥ 3)
URL: https://ericgiunta.github.io/Colossus/, https://github.com/ericgiunta/Colossus
NeedsCompilation: yes
SystemRequirements: make
Language: en-US
Citation: Colossus citation info
Materials: README NEWS
CRAN checks: Colossus results

Documentation:

Reference manual: Colossus.pdf
Vignettes: Distributed Start Framework (source, R code)
Alternative Regression Options (source, R code)
List of Control Options (source, R code)
Dose Response Formula Terms (source, R code)
Excess and Predicted Cases (source, R code)
Multiple Realization Methods (source, R code)
Functions for Plotting and Analysis (source, R code)
Script comparisons with 32-bit Epicure (source, R code)
Colossus Description (source, R code)
Time Dependent Covariate Use (source, R code)
Confidence Interval Selection (source, R code)

Downloads:

Package source: Colossus_1.1.4.2.tar.gz
Windows binaries: r-devel: Colossus_1.1.4.2.zip, r-release: Colossus_1.1.4.2.zip, r-oldrel: Colossus_1.1.4.2.zip
macOS binaries: r-release (arm64): Colossus_1.1.4.2.tgz, r-oldrel (arm64): Colossus_1.1.4.2.tgz, r-release (x86_64): Colossus_1.1.4.2.tgz, r-oldrel (x86_64): Colossus_1.1.4.2.tgz
Old sources: Colossus archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=Colossus to link to this page.

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.
Health stats visible at Monitor.