SCM

R Development Page

Contributed R Packages

Below is a list of all packages provided by project topmodels: Enhanced Model Infrastructure.

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

brtobit

Bias-Reduced Tobit Regression Models

  Bias-reducted tobit regression models are Gaussian regression models with a response variable left-censored at zero, constant latent variance, and a latent mean that depends on covariates through a linear predictor. Instead of estimating the parameters by plain maximum likelihood a bias-reduced estimator is employed.
  Version: 0.1-1 | Last change: 2021-01-19 04:16:50+01 | Rev.: 1146
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current
  R install command: install.packages("brtobit", repos="http://R-Forge.R-project.org")
 
Logs:  
Package build: Source package (Linux x86_64) Windows binary (x86_64/i386)
Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)


crch

Censored Regression with Conditional Heteroscedasticity

  Different approaches to censored or truncated regression with conditional heteroscedasticity are provided. First, continuous distributions can be used for the (right and/or left censored or truncated) response with separate linear predictors for the mean and variance. Second, cumulative link models for ordinal data (obtained by interval-censoring continuous data) can be employed for heteroscedastic extended logistic regression (HXLR). In the latter type of models, the intercepts depend on the thresholds that define the intervals.
  Version: 1.0-4 | Last change: 2019-08-21 08:16:50+02 | Rev.: 1141
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get crch 1.0-4 from CRAN
  R install command: install.packages("crch", repos="http://R-Forge.R-project.org")
 
Logs:  
Package build: Source package (Linux x86_64) Windows binary (x86_64/i386)
Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)


topmodels

Infrastructure for Inference and Forecasting in Probabilistic Models

  Unified infrastructure for probabilistic models and distributional regressions: Computations of probabilities, densities, scores, and Hessians. Probabilistic forecasting. Diagnostic graphics like rootograms, PIT histograms, reliagrams (reliability diagrams), (randomized) quantile residual Q-Q plots.
  Version: 0.1-0 | Last change: 2021-11-22 16:40:20+01 | Rev.: 1473
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current
  R install command: install.packages("topmodels", repos="http://R-Forge.R-project.org")
 
Logs:  
Package build: Source package (Linux x86_64) Windows binary (x86_64/i386)
Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)

 

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.
5 - Offline: the package is not available. The build system may be offline or the package maintainer did not trigger a rebuild (done e.g., via committing to the package repository).

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