Package: deeptrafo 1.0-0

Lucas Kook

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, 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>).

Authors:Lucas Kook [aut, cre], Philipp Baumann [aut], David Ruegamer [aut]

# Install 'deeptrafo' in R:

install.packages('deeptrafo', repos = c('https://neural-structured-additive-learning.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Last updated 1 months agofrom:d6221da6c3. Checks:5 OK. Indexed: yes.

Help page	Topics
Initializes the Processed Additive Predictor for ATMs	atm_init
BoxCox-type neural network transformation models	BoxCoxNN
S3 methods for deep conditional transformation models	coef.deeptrafo fitted.deeptrafo logLik.deeptrafo predict.deeptrafo print.deeptrafo residuals.deeptrafo simulate.deeptrafo summary.deeptrafo
Deep continuous outcome logistic regression	ColrNN
Deep distribution-free count regression	cotramNN
Cox proportional hazards type neural network transformation models	CoxphNN
Deep conditional transformation models with alternative formula interface	dctm
Deep Conditional Transformation Models	deeptrafo
Deep ensembling for neural network transformation models	ensemble.deeptrafo
Define Predictor of Transformation Model	from_preds_to_trafo
Initializes the Processed Additive Predictor for TM's Interaction	h1_init
Lehmann-type neural network transformation models	LehmanNN
Deep normal linear regression	LmNN
Generic negative log-likelihood for transformation models	nll
Ordinal neural network transformation models	ontram
Plot method for deep conditional transformation models	plot.deeptrafo
Deep (proportional odds) logistic regression	PolrNN
Deep parametric survival regression	SurvregNN
Options for transformation models	trafo_control
Transformation ensembles	trafoensemble
Tune and evaluate weighted transformation ensembles	weighted_logLik