R Development Page
Contributed R Packages
Below is a list of all packages provided by project Regression Models for Ordinal Data.
Important note for package binaries: R-Forge provides these binaries only for the most recent version of R, but not for older versions. In order to successfully install the packages provided on R-Forge, you have to switch to the most recent version of R or, alternatively, install from the package sources (.tar.gz).
Packages
| Rufus | Runes Utility Functions | |||||||||||
| This package contains various utility functions. | ||||||||||||
| Version: 0.1-1 | Last change: 2014-12-29 19:27:35+01 | Rev.: 173 | ||||||||||||
Download:
 (.tar.gz) |
 (.zip) |
Build status: Failed to build | ||||||||||||
R install command:
install.packages("Rufus", repos="http://R-Forge.R-project.org") | ||||||||||||
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| ordinal | Regression Models for Ordinal Data | |||||||||
| Implementation of cumulative link (mixed) models also known as ordered regression models, proportional odds models, proportional hazards models for grouped survival times and ordered logit/probit/... models. Estimation is via maximum likelihood and mixed models are fitted with the Laplace approximation and adaptive Gauss-Hermite quadrature. Multiple random effect terms are allowed and they may be nested, crossed or partially nested/crossed. Restrictions of symmetry and equidistance can be imposed on the thresholds (cut-points/intercepts). Standard model methods are available (summary, anova, drop-methods, step, confint, predict etc.) in addition to profile methods and slice methods for visualizing the likelihood function and checking convergence. | ||||||||||
| Version: 2016.12-12 | Last change: 2016-12-12 20:51:06+01 | Rev.: 184 | ||||||||||
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Download:
(.tar.gz) |
(.zip) |
Build status: Current | Stable Release: Get ordinal 2019.4-25 from CRAN | ||||||||||
R install command:
install.packages("ordinal", repos="http://R-Forge.R-project.org") | ||||||||||
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| ordinal2 | Regression Models for Ordinal Data | |||||||||
| This package implements cumulative link (mixed) models also known as ordered regression models, proportional odds models, proportional hazards models for grouped survival times and ordered logit/probit/... models. Estimation is via maximum likelihood and mixed models are fitted with the Laplace approximation. Multiple random effect terms are allowed and they may be nested, crossed or partially nested/crossed. Restrictions of symmetry and equidistance can be imposed on the thresholds (cut-points). Standard model methods are available (summary, anova, drop-methods, step, confint etc.) in addition to profile methods and slice methods for visualizing the likelihood function and checking convergence. | ||||||||||
| Version: 2011.06-9 | Last change: 2012-05-09 14:10:10+02 | Rev.: 74 | ||||||||||
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Download:
(.tar.gz) |
(.zip) |
Build status: Current | ||||||||||
R install command:
install.packages("ordinal2", repos="http://R-Forge.R-project.org") | ||||||||||
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Build status codes
0 - Current: the package is available for download. The corresponding package passed checks on the Linux and Windows platform without ERRORs.
1 - Scheduled for build: the package has been recognized by the build system and provided in the staging area.
2 - Building: the package has been sent to the build machines. It will be built and checked using the latest patched version of R. Note that it is included in a batch of several packages. Thus, this process will take some time to finish.
3 - Failed to build: the package failed to build or did not pass the checks on the Linux and/or Windows platform. It is not made available since it does not meet the policies.
4 - Conflicts: two or more packages of the same name exist. None of them will be built. Maintainers are asked to negotiate further actions.
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