deeptrafo: Fitting Deep Conditional Transformation Models

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, 2022, <doi:10.48550/arXiv.2110.08248>) and transformation ensembles (Kook et al, 2022, <doi:10.48550/arXiv.2205.12729>) are implemented.

Version:	0.1-1
Depends:	R (≥ 4.0.0), Formula, tensorflow (≥ 2.2.0), keras (≥ 2.2.0), tfprobability (≥ 0.15), deepregression
Imports:	mlt, variables, stats, purrr, survival, R6, reticulate
Suggests:	testthat, knitr, ordinal, tram, cotram, covr
Published:	2022-11-22
DOI:	10.32614/CRAN.package.deeptrafo
Author:	Lucas Kook [aut, cre], Philipp Baumann [aut], David Ruegamer [aut]
Maintainer:	Lucas Kook <lucasheinrich.kook at gmail.com>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	deeptrafo results

Documentation:

Reference manual:

deeptrafo.pdf

Downloads:

Package source:	deeptrafo_0.1-1.tar.gz
Windows binaries:	r-devel: deeptrafo_0.1-1.zip, r-release: deeptrafo_0.1-1.zip, r-oldrel: deeptrafo_0.1-1.zip
macOS binaries:	r-release (arm64): deeptrafo_0.1-1.tgz, r-oldrel (arm64): deeptrafo_0.1-1.tgz, r-release (x86_64): deeptrafo_0.1-1.tgz, r-oldrel (x86_64): deeptrafo_0.1-1.tgz
Old sources:	deeptrafo archive

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