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) <doi:10.48550/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.
Version: 1.0 Imports: keras, tensorflow, fda.usc, fda, ggplot2, ggpubr, caret, pbapply, reshape2, flux, doParallel, foreach, Matrix Suggests: knitr, rmarkdown Published: 2020-09-15 DOI: 10.32614/CRAN.package.FuncNN Author: Richard Groenewald [ctb], Barinder Thind [aut, cre, cph], Jiguo Cao [aut], Sidi Wu [ctb] Maintainer: Barinder Thind <barinder.thi at gmail.com> License: GPL-3 URL: https://arxiv.org/abs/2006.09590, https://github.com/b-thi/FuncNN NeedsCompilation: no Citation: FuncNN citation info Materials: README CRAN checks: FuncNN results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=FuncNN to link to this page.
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