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: RForge 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 RForge, you have to switch to the most recent version of R or, alternatively, install from the package sources (.tar.gz).
Packages
brtobit  BiasReduced Tobit Regression Models  
Biasreducted tobit regression models are Gaussian regression models with a response variable leftcensored 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 biasreduced estimator is employed.  
Version: 0.11  Last change: 20210119 04:16:50+01  Rev.: 1146  
Download: (.tar.gz)  (.zip)  Build status: Current  
R install command:
install.packages("brtobit", repos="http://RForge.Rproject.org")  

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 intervalcensoring 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. Infrastructure for working with censored or truncated normal, logistic, and Studentt distributions, i.e., d/p/q/r functions and distributions3 objects.  
Version: 1.13  Last change: 20240209 02:45:29+01  Rev.: 1763  
Download: (.tar.gz)  (.zip)  Build status: Current  Stable Release: Get crch 1.12 from CRAN  
R install command:
install.packages("crch", repos="http://RForge.Rproject.org")  

topmodels  Infrastructure for Forecasting and Assessment of Probabilistic Models  
Unified infrastructure for probabilistic models and distributional regressions: Probabilistic forecasting of insample and outofsample of probabilities, densities, quantiles, and moments. Probabilistic scoring via logscore (loglikelihood), (continuous) ranked probability score, etc. Diagnostic graphics like rootograms, PIT histograms, (randomized) quantile residual QQ plots, and reliagrams (reliability diagrams).  
Version: 0.30  Last change: 20240419 03:03:33+02  Rev.: 1773  
Download: (.tar.gz)  (.zip)  Build status: Current  
R install command:
install.packages("topmodels", repos="http://RForge.Rproject.org")  

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.
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