Package: FuncNN
Title: Functional Neural Networks
Version: 1.0
Authors@R: c(
    person("Richard", "Groenewald", role = "ctb"),
    person("Barinder", "Thind", email = "barinder.thi@gmail.com", role = c("aut", "cre", "cph")),
    person("Jiguo", "Cao", role = "aut"),
    person("Sidi Wu", role = "ctb")
    )
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.
Imports: keras, tensorflow, fda.usc, fda, ggplot2, ggpubr, caret,
        pbapply, reshape2, flux, doParallel, foreach, Matrix
URL: https://arxiv.org/abs/2006.09590, https://github.com/b-thi/FuncNN
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2020-09-07 23:52:53 UTC; Richard
Author: Richard Groenewald [ctb],
  Barinder Thind [aut, cre, cph],
  Jiguo Cao [aut],
  Sidi Wu [ctb]
Maintainer: Barinder Thind <barinder.thi@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-15 09:40:15 UTC
Built: R 4.0.2; ; 2020-09-16 11:12:37 UTC; unix
