atm_init

Initializes the Processed Additive Predictor for ATMs

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

atm_init function

<dl><dt>atmnr, h1nr</dt>
<dd>positions of the atm and h1 formula</dd></dl>

Arguments

Initializes the Processed Additive Predictor for ATMs — atm_init

<dl>

<dt>atmnr, h1nr</dt>
<dd>positions of the atm and h1 formula</dd>

</dl>

atm_init: Initializes the Processed Additive Predictor for ATMs

Description

Usage

Value

Arguments