Package: deepregression
Title: Fitting Deep Distributional Regression
Version: 1.0.0
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. (2023) <doi:10.18637/jss.v105.i02>.
    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 = "2.10.0", pip =
        TRUE), list(package = "tensorflow_probability", version =
        "0.16", pip = TRUE), list(package = "keras", version =
        "2.10.0", pip = TRUE)) )
Depends: R (>= 4.0.0), tensorflow (>= 2.2.0), tfprobability, keras (>=
        2.2.0)
Suggests: testthat, knitr, covr
Imports: mgcv, dplyr, R6, reticulate (>= 1.14), Matrix, magrittr,
        tfruns, methods
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.1.2
NeedsCompilation: no
Packaged: 2023-01-17 22:28:56 UTC; david
Author: David Ruegamer [aut, cre],
  Florian Pfisterer [ctb],
  Philipp Baumann [ctb],
  Chris Kolb [ctb],
  Lucas Kook [ctb]
Maintainer: David Ruegamer <david.ruegamer@gmail.com>
Repository: CRAN
Date/Publication: 2023-01-17 22:50:08 UTC
Built: R 4.2.0; ; 2023-07-11 03:14:30 UTC; unix
