ctm
SCM

R Development Page

Contributed R Packages

Below is a list of all packages provided by project ctm.

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

basefun

Infrastructure for Computing with Basis Functions

  Some very simple infrastructure for basis functions.
  Version: 1.0-7 | Last change: 2020-02-13 17:45:04+01 | Rev.: 1388
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get basefun 1.0-7 from CRAN
  R install command: install.packages("basefun", 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)


cotram

Count Transformation Models

  Count transformation models featuring parameters interpretable as discrete hazard ratios, odds ratios, reverse-time discrete hazard ratios, or transformed expectations. An appropriate data transformation for a count outcome and regression coefficients are simultaneously estimated by maximising the exact discrete log-likelihood using the computational framework provided in package mlt, technical details are given in Siegfried & Hothorn (2020) .
  Version: 0.2-0 | Last change: 2020-03-30 20:33:48+02 | Rev.: 1432
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get cotram 0.2-0 from CRAN
  R install command: install.packages("cotram", 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)


ctm

Conditional Transformation Models

  An experimental implementation of conditional transformation models for the semiparametric estimation of conditional distribution functions. Contains example analyses and a simulation study.
  Version: 0.0-3 | Last change: 2013-11-11 14:50:25+01 | Rev.: 59
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current
  R install command: install.packages("ctm", 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)


ctmDevel

Conditional Transformation Models

  An experimental implementation of conditional transformation models for the semiparametric estimation of conditional distribution functions. Contains example analyses and a simulation study.
  Version: 0.1-0 | Last change: 2014-08-14 16:07:03+02 | Rev.: 64
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current
  R install command: install.packages("ctmDevel", 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)


mlt

Most Likely Transformations

  Likelihood-based estimation of conditional transformation models via the most likely transformation approach described in Hothorn et al. (2018) .
  Version: 1.2-1 | Last change: 2020-05-13 17:42:27+02 | Rev.: 1448
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get mlt 1.2-0 from CRAN
  R install command: install.packages("mlt", 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)


mlt.docreg

Most Likely Transformations: Documentation and Regression Tests

  Additional documentation, a package vignette and regression tests for package mlt.
  Version: 1.0-5 | Last change: 2020-02-13 17:45:04+01 | Rev.: 1388
  Download: linux(.tar.gz) | windows(.zip) | Build status: Failed to build | Stable Release: Get mlt.docreg 1.0-5 from CRAN
  R install command: install.packages("mlt.docreg", 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)


tbm

Transformation Boosting Machines

  Boosting the likelihood of conditional and shift transformation models.
  Version: 0.3-2 | Last change: 2019-12-11 15:48:40+01 | Rev.: 1323
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get tbm 0.3-2.1 from CRAN
  R install command: install.packages("tbm", 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)


tram

Transformation Models

  Formula-based user-interfaces to specific transformation models implemented in package mlt. Available models include Cox models, some parametric survival models (Weibull, etc.), models for ordered categorical variables, normal and non-normal (Box-Cox type) linear models, and continuous outcome logistic regression (Lohse et al., 2017, ). The underlying theory is described in Hothorn et al. (2018) . An extension to transformation models for clustered data is provided (Hothorn, 2019, ). Multivariate conditional transformation models () can be fitted as well.
  Version: 0.4-1 | Last change: 2020-07-10 15:02:17+02 | Rev.: 1475
  Download: linux(.tar.gz) | windows(.zip) | Build status: Failed to build | Stable Release: Get tram 0.4-0 from CRAN
  R install command: install.packages("tram", 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)


tramME

Transformation Models with Mixed Effects

  Likelihood-based estimation of mixed-effects transformation models using the Template Model Builder (TMB). The technical details of transformation models are given in Hothorn et al. (2018) . The random effects are assumed to be normally distributed on the scale of the transformation function, the marginal likelihood is evaluated using the Laplace approximation, and the gradients are calculated with automatic differentiation (AD).
  Version: 0.0.2 | Last change: 2020-04-06 14:23:48+02 | Rev.: 1434
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get tramME 0.0.2 from CRAN
  R install command: install.packages("tramME", 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)


tramnet

Penalized Transformation Models

  Partially penalized versions of specific transformation models implemented in package mlt. Available models include a fully parametric version of the Cox model, other parametric survival models (Weibull, etc.), models for binary and ordered categorical variables, normal and transformed-normal (Box-Cox type) linear models, and continuous outcome logistic regression. Hyperparameter tuning is facilitated through model-based optimization functionalities from package mlrMBO. The accompanying vignette describes the methodology used in tramnet in detail. Transformation models and model-based optimization are described in Hothorn et al. (2019) and Bischl et al. (2016) , respectively.
  Version: 0.0-3 | Last change: 2020-05-14 12:46:17+02 | Rev.: 1449
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get tramnet 0.0-3 from CRAN
  R install command: install.packages("tramnet", 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)


trtf

Transformation Trees and Forests

  Recursive partytioning of transformation models with corresponding random forest for conditional transformation models as described in Transformation Forests (Hothorn and Zeileis, 2017, ) and Top-Down Transformation Choice (Hothorn, 2018, ).
  Version: 0.3-7 | Last change: 2020-04-22 10:27:51+02 | Rev.: 1437
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get trtf 0.3-7 from CRAN
  R install command: install.packages("trtf", 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)


variables

Variable Descriptions

  Abstract descriptions of (yet) unobserved variables.
  Version: 1.0-3 | Last change: 2020-02-13 17:45:04+01 | Rev.: 1388
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get variables 1.0-3 from CRAN
  R install command: install.packages("variables", 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

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