Fitting Deep Distributional Regression

Allows for the specification of semi-structured deep distributional regression models which are fitted in a neural network as proposed by Ruegamer et al. (2021) . Predictors can be modeled using structured (penalized) linear effects, structured non-linear effects or using an unstructured deep network model.


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install.packages("deepregression")

0.1 by David Ruegamer, 17 days ago


Browse source code at https://github.com/cran/deepregression


Authors: David Ruegamer [aut, cre] , Florian Pfisterer [ctb] , Philipp Baumann [ctb] , Chris Kolb [ctb]


Documentation:   PDF Manual  


GPL-3 license


Imports tensorflow, tfprobability, keras, mgcv, dplyr, purrr, R6, reticulate, Matrix, magrittr, Metrics, tfruns, methods, utils

Suggests testthat, knitr


See at CRAN