Package: tramnet 0.1-1
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 'mlr3MBO'. The methodology is described in Kook et al. (2021) <doi:10.32614/RJ-2021-054>. Transformation models and model-based optimization are described in Hothorn et al. (2019) <doi:10.1111/sjos.12291> and Bischl et al. (2016) <doi:10.48550/arXiv.1703.03373>, respectively.
Authors:
tramnet_0.1-1.tar.gz
tramnet_0.1-1.zip(r-4.7)tramnet_0.1-1.zip(r-4.6)tramnet_0.1-1.zip(r-4.5)
tramnet_0.1-1.tgz(r-4.6-any)tramnet_0.1-1.tgz(r-4.5-any)
tramnet_0.1-1.tar.gz(r-4.7-any)tramnet_0.1-1.tar.gz(r-4.6-any)
tramnet_0.1-1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
tramnet/json (API)
NEWS
| # Install 'tramnet' in R: |
| install.packages('tramnet', repos = c('https://r-forge.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://r-forge.r-project.org/projects/ctm
Last updated from:6cd3bd0ce8. Checks:7 ERROR, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | ERROR | 182 | ||
| source / vignettes | OK | 213 | ||
| linux-release-x86_64 | ERROR | 193 | ||
| macos-release-arm64 | ERROR | 147 | ||
| macos-oldrel-arm64 | ERROR | 116 | ||
| windows-devel | ERROR | 111 | ||
| windows-release | ERROR | 112 | ||
| windows-oldrel | ERROR | 133 | ||
| wasm-release | OK | 140 |
Exports:BoxCoxNETColrNETCoxphNETcvl_tramnetLehmannNETLmNETmbo_recommendedmbo_tramnetplot_pathPolrNETprof_alphaprof_lambdaSurvregNETtramnet
Dependencies:alabamabackportsbasefunBBbbotkcheckmateclarabelclicodacodetoolsconeprojCVXRdata.tabledigestevaluateforeachFormulafuturefuture.applyglobalsgmphighsicenRegiteratorslatticelgrlistenvMASSMatrixmiraimlbenchMLEcensmlr3mlr3mbomlr3measuresmlr3miscmlr3tuningmltmultcompmvtnormnanonextnloptrnumDerivorthopolynomosqppalmerpenguinsparadoxparallellypolynomPRROCquadprogR6RcppRcppArmadilloRcppEigenrlangS7sandwichscsslamspacefillrsurvivalTH.datatramuuidvariableszoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Cross-validating tramnet models | cvl_tramnet |
| Regularized transformation model classes | BoxCoxNET ColrNET CoxphNET LehmannNET LmNET PolrNET SurvregNET |
| S3 methods for class '"tramnet"' | coef.tramnet coef.tramnet_Lm estfun.tramnet logLik.tramnet predict.tramnet print.summary.tramnet print.tramnet residuals.tramnet simulate.tramnet summary.tramnet |
| Fit recommended regularized tram based on model based optimization output | mbo_recommended |
| Model based optimization for regularized transformation models | mbo_tramnet |
| Plot regularization paths | plot_path |
| Plot '"tramnet"' objects | plot.tramnet |
| Profiling tuning parameters | prof_alpha |
| Profiling tuning parameters | prof_lambda |
| Regularized transformation models | tramnet tramnet.formula tramnet.tram |
