_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-nnfor 0.9.9
Propagated dependencies: r-uroot@2.1-3 r-tsutils@0.9.4 r-plotrix@3.8-4 r-neuralnet@1.44.2 r-mass@7.3-61 r-glmnet@4.1-8 r-generics@0.1.3 r-forecast@8.23.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://kourentzes.com/forecasting/2019/01/16/tutorial-for-the-nnfor-r-package/
Licenses: GPL 3
Synopsis: Time Series Forecasting with Neural Networks
Description:

Automatic time series modelling with neural networks. Allows fully automatic, semi-manual or fully manual specification of networks. For details of the specification methodology see: (i) Crone and Kourentzes (2010) <doi:10.1016/j.neucom.2010.01.017>; and (ii) Kourentzes et al. (2014) <doi:10.1016/j.eswa.2013.12.011>.

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