Fitting Deep Conditional Transformation Models

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Documentation for package ‘deeptrafo’ version 0.1-1

• DESCRIPTION file.

Help Pages

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