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deepregression: 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. (2023) <doi:10.18637/jss.v105.i02>. Predictors can be modeled using structured (penalized) linear effects, structured non-linear effects or using an unstructured deep network model.
Getting started
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Package details |
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| Author | David Ruegamer [aut, cre], Christopher Marquardt [ctb], Laetitia Frost [ctb], Florian Pfisterer [ctb], Philipp Baumann [ctb], Chris Kolb [ctb], Lucas Kook [ctb] |
| Maintainer | David Ruegamer <david.ruegamer@gmail.com> |
| License | GPL-3 |
| Version | 2.3.2 |
| Package repository | View on CRAN |
| Installation |
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