Single-Index Neural Network for Skewed Heavy-Tailed Data

Provides a deep neural network model with a monotonic increasing single index function tailored for periodontal disease studies. The residuals are assumed to follow a skewed T distribution, a skewed normal distribution, or a normal distribution. More details can be found at Liu, Wang, Bai and Bandyopadhyay (2026) .


Reference manual

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install.packages("DNNSIM")

0.2.1 by Qingyang Liu, 7 days ago


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


Authors: Qingyang Liu [aut, cre] (ORCID: , Shijie Wang [aut] , Ray Bai [aut] , Dipankar Bandyopadhyay [aut]


Documentation:   PDF Manual  


GPL (>= 3) license


Imports reticulate, stats, Rdpack

System requirements: Python (>= 3.8.0); PyTorch (https://pytorch.org/); NumPy (https://numpy.org/); SciPy (https://scipy.org/); sklearn (https://scikit-learn.org/stable/);


See at CRAN