Package: tramnet 0.1-0
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.), normal and transformed-normal (Box-Cox type) linear models, and continuous outcome logistic regression. Models can be specified via a formula interface. Hyperparameter tuning is facilitated through model-based optimization functionalities from package 'mlr3mbo'. The accompanying vignette describes the methodology used in 'tramnet' in detail. Transformation models and model-based optimization are described in Hothorn et al. (2019) <doi:10.1111/sjos.12291> and Bischl et al. (2017) <doi:10.48550/arXiv.1703.03373>, respectively.
Authors:
tramnet_0.1-0.tar.gz
tramnet_0.1-0.zip(r-4.7-any)tramnet_0.1-0.zip(r-4.6-any)tramnet_0.1-0.zip(r-4.5-any)
tramnet_0.1-0.tgz(r-4.6-any)tramnet_0.1-0.tgz(r-4.5-any)
tramnet_0.1-0.tar.gz(r-4.7-any)tramnet_0.1-0.tar.gz(r-4.6-any)
tramnet_0.1-0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
tramnet/json (API)
| # Install 'tramnet' in R: |
| install.packages('tramnet', repos = c('https://lucaskook.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://codeberg.org/lucaskook/tramnet
Last updated from:2521887fb1. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 223 | ||
| source / vignettes | OK | 258 | ||
| linux-release | OK | 215 | ||
| macos-release | OK | 218 | ||
| macos-oldrel | OK | 201 | ||
| windows-devel | OK | 158 | ||
| windows-release | OK | 144 | ||
| windows-oldrel | OK | 149 | ||
| wasm-release | OK | 170 |
Exports:BoxCoxnetColrnetCoxphnetcvl_tramnetelnet_objlasso_objLehmannnetLmnetmbo_recommendedmbo_tramnetplot_pathprof_alphaprof_lambdaridge_objSurvregnettramnet
Dependencies:alabamabackportsbasefunBBbbotkcheckmateclarabelclicodacodetoolsconeprojCVXRdata.tabledigestevaluateforeachFormulafuturefuture.applyglobalsgmphighsicenRegiteratorslatticelgrlhslistenvMASSMatrixmatrixStatsmiraimlbenchMLEcensmlr3mlr3learnersmlr3mbomlr3measuresmlr3miscmlr3tuningmltmoocoremultcompmvtnormnanonextnloptrnumDerivorthopolynomosqppalmerpenguinsparadoxparallellypolynomPRROCquadprogR6rbibutilsRcppRcppArmadilloRcppEigenRdpackrlangS7sandwichscsslamspacefillrsurvivalTH.datatramuuidvariableszoo
