from_preds_to_trafo

Define Predictor of Transformation Model

Allows for the specification of deep conditional transformation
models (DCTMs) and ordinal neural network transformation models, as
described in Baumann et al (2021) <doi:10.1007/978-3-030-86523-8_1> and
Kook et al (2022) <doi:10.1016/j.patcog.2021.108263>. Extensions such as
autoregressive DCTMs (Ruegamer et al, 2023, <doi:10.1007/s11222-023-10212-8>)
and transformation ensembles (Kook et al, 2022, <doi:10.48550/arXiv.2205.12729>)
are implemented. The software package is described in Kook et al (2024,
<doi:10.18637/jss.v111.i10>).

Lucas Kook

deeptrafo

Fitting Deep Conditional Transformation Models

Philipp Baumann

David Ruegamer

from_preds_to_trafo function

<dl><dt>atm_toplayer</dt>
<dd>Function to be applied on top of the transformed lags.</dd>
<dt>const_ia</dt>
<dd>See <code>addconst_interaction</code> in <code>deeptrafo</code>
or <code>deepregression</code>.</dd>
<dt>...</dt>
<dd>For compatibility with 'deepregression'</dd></dl>

Arguments

Define Predictor of Transformation Model — from_preds_to_trafo

<dl>

<dt>atm_toplayer</dt>
<dd>Function to be applied on top of the transformed lags.</dd>


<dt>const_ia</dt>
<dd>See <code>addconst_interaction</code> in <code>deeptrafo</code>
or <code>deepregression</code>.</dd>


<dt>...</dt>
<dd>For compatibility with 'deepregression'</dd>

</dl>

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from_preds_to_trafo: Define Predictor of Transformation Model

Description

Usage

Value

Arguments

Details