mbo_recommended

Extracts the "optimal" tuning parameters from an object of class
<code>"MBOSingleObjResult"</code> and fits the corresponding <code>tramnet</code> model

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) <arxiv:1703.03373>, respectively.

Lucas Kook

tramnet

Penalized Transformation Models

Balint Tamasi

Sandra Siegfried

Samuel Pawel

Torsten Hothorn

mbo_recommended function

<dl><dt>mbo_obj</dt>
<dd>object return by <code>mbo_tramnet</code></dd>
<dt>m0</dt>
<dd>null model of class <code>"tram"</code></dd>
<dt>x</dt>
<dd>matrix of covariables</dd>
<dt>...</dt>
<dd>additional arguments to <code>tramnet()</code></dd></dl>

Arguments

Fit recommended regularized tram based on model based optimization output — mbo_recommended

<dl>

<dt>mbo_obj</dt>
<dd>object return by <code>mbo_tramnet</code></dd>


<dt>m0</dt>
<dd>null model of class <code>"tram"</code></dd>


<dt>x</dt>
<dd>matrix of covariables</dd>


<dt>...</dt>
<dd>additional arguments to <code>tramnet()</code></dd>

</dl>

mbo_recommended: Fit recommended regularized tram based on model based optimization output

Description

Usage

Value

Arguments