FuncNN-package {FuncNN} | R Documentation |
FuncNN: Functional Neural Networks
Description
A collection of functions which fit functional neural network models. In other words, this package will allow users to build deep learning models that have either functional or scalar responses paired with functional and scalar covariates. We implement the theoretical discussion found in Thind, Multani and Cao (2020) <arXiv:2006.09590> through the help of a main fitting and prediction function as well as a number of helper functions to assist with cross-validation, tuning, and the display of estimated functional weights.
Author(s)
Maintainer: Barinder Thind barinder.thi@gmail.com [copyright holder]
Authors:
Jiguo Cao
Other contributors:
Richard Groenewald [contributor]
Sidi Wu [contributor]
References
Thind, B., Multani, K., and Cao J. (2020) “Deep Learning with Functional Inputs”, https://arxiv.org/abs/2006.09590
See Also
Useful links: