Deepregression: Fitting Semi-Structured Deep Distributional Regression in R

MCML Authors

David Rügamer

Prof. Dr.

Core PI

Statistics, Data Science and Machine Learning

Florian Pfisterer

Dr.

* Former Member

→ Group Bernd Bischl
 Statistical Learning and Data Science

Abstract

Allows for the specification of semi-structured deep distributional regression models which are fitted in a neural network as proposed by Ruegamer et al. (2023). Predictors can be modeled using structured (penalized) linear effects, structured non-linear effects or using an unstructured deep network model.

manual RSB+21a

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SW Package

Jan. 2021

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Authors

D. Rügamer • F. Pfisterer • P. Baumann

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Links

URL

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Research Area

 A1 | Statistical Foundations & Explainability