DESCRIPTION

Package: deepregression
Title: Fitting Deep Distributional Regression
Version: 0.2
Authors@R: c(
    person("David", "Ruegamer", , "david.ruegamer@gmail.com", role = c("aut", "cre")),
    person("Florian", "Pfisterer", , "florian.pfisterer@stat.uni-muenchen.de", role = c("ctb")),
    person("Philipp", "Baumann", , "baumann@kof.ethz.ch", role = c("ctb")),
    person("Chris", "Kolb", , "chris.kolb@stat.uni-muenchen.de", role = c("ctb")),
    person("Lucas", "Kook", , "lucasheinrich.kook@uzh.ch", role = c("ctb")))
Description:
    Allows for the specification of semi-structured deep distributional regression models which are fitted in a neural network as 
    proposed by Ruegamer et al. (2021) <arXiv:2104.02705>.
    Predictors can be modeled using structured (penalized) linear effects, structured non-linear effects or using an unstructured deep network model.
Config/reticulate:
  list(
    packages = list(
      list(package = "six", pip = TRUE),
      list(package = "tensorflow", version = "2.8.0", pip = TRUE),
      list(package = "tensorflow_probability", version = "0.16", pip = TRUE),
      list(package = "keras", version = "2.8.0", pip = TRUE))
  )
Depends: R (>= 4.0.0)
Suggests:
    testthat,
    knitr,
    covr
Imports:
    tensorflow (>= 2.2.0),
    tfprobability,
    keras (>= 2.2.0),
    mgcv,
    dplyr,
    purrr,
    R6,
    reticulate (>= 1.14),
    Matrix,
    magrittr,
    Metrics,
    tfruns,
    methods,
    utils
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.2