estfun.tramnet

<code>estfun</code> method for class <code>"tramnet"</code> which computes
the score contributions w.r.t. each model parameter.

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

estfun.tramnet function

<dl><dt>x</dt>
<dd>object of class <code>"tramnet"</code></dd>
<dt>parm</dt>
<dd>parameters for evaluating the score</dd>
<dt>w</dt>
<dd>weights</dd>
<dt>newdata</dt>
<dd>data on which to compute the score contributions</dd>
<dt>...</dt>
<dd>additional arguments to <code>estfun</code></dd></dl>

Arguments

Author

estfun method for class "tramnet" — estfun.tramnet

<dl>

<dt>x</dt>
<dd>object of class <code>"tramnet"</code></dd>


<dt>parm</dt>
<dd>parameters for evaluating the score</dd>


<dt>w</dt>
<dd>weights</dd>


<dt>newdata</dt>
<dd>data on which to compute the score contributions</dd>


<dt>...</dt>
<dd>additional arguments to <code>estfun</code></dd>

</dl>

estfun.tramnet: estfun method for class `"tramnet"`

Description

Usage

Value

Arguments

Author