Penalized Transformation Models
Profiling tuning parameters
residuals method for class "tramnet"
Ridge objective function for model based optimization
simulate method for class "tramnet"
summary method for class "tramnet"
logLik method for class "tramnet"
Fit recommended regularized tram based on model based optimization out...
Lasso objective function for model based optimization
coef method for class "tramnet_Lm"
coef method for class "tramnet"
Cross validation for "tramnet" models
Elastic net objective function for model based optimization
estfun method for class "tramnet"
Model based optimization for regularized transformation models
Plot regularization paths for "prof_*" classes
plot method for class "tramnet"
predict method for class "tramnet"
print summary method for class "tramnet"
print method for class "tramnet"
Profiling tuning parameters
Regularised 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) <doi:10.1111/sjos.12291> and Bischl et al. (2016) <doi:10.48550/arXiv.1703.03373>, respectively.