Package: smoots
Type: Package
Title: Nonparametric Estimation of the Trend and Its Derivatives in TS
Version: 1.1.4
Description: The nonparametric trend and its derivatives in equidistant time 
    series (TS) with short-memory stationary errors can be estimated. The 
    estimation is conducted via local polynomial regression using an 
    automatically selected bandwidth obtained by a built-in iterative plug-in 
    algorithm or a bandwidth fixed by the user. A Nadaraya-Watson kernel 
    smoother is also built-in as a comparison. With version 1.1.0, a linearity 
    test for the trend function, forecasting methods and backtesting 
    approaches are implemented as well.
    The smoothing methods of the package are described in Feng, Y., Gries, T., 
    and Fritz, M. (2020) <doi:10.1080/10485252.2020.1759598>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.3
Imports: stats, utils, graphics, grDevices, Rcpp (>= 1.0.7), future (>=
        1.22.1), future.apply (>= 1.8.1), progressr (>= 0.8.0),
        progress (>= 1.2.2)
Suggests: knitr, rmarkdown, fGarch, RcppArmadillo (>= 0.10.6.0.0),
        testthat (>= 3.0.0)
LinkingTo: Rcpp, RcppArmadillo
Depends: R (>= 2.10)
Authors@R: 
    c(person(given = "Yuanhua",
             family = "Feng",
             role = "aut",
             comment = "Paderborn University, Germany"),
      person(given = "Sebastian",
             family = "Letmathe",
             role = "aut",
             comment = "Paderborn University, Germany"),
      person(given = "Dominik",
             family = "Schulz",
             role = c("aut", "cre"),
             email = "schulzd@mail.uni-paderborn.de",
             comment = "Paderborn University, Germany"),
      person(given = "Thomas",
             family = "Gries",
             role = "ctb",
             comment = "Paderborn University, Germany"),
      person(given = "Marlon",
             family = "Fritz",
             role = "ctb",
             comment = "Paderborn University, Germany"))
URL: https://wiwi.uni-paderborn.de/en/dep4/feng/
        https://wiwi.uni-paderborn.de/dep4/gries/
Acknowledgments: This work was supported by the German DFG project
        GZ-FE-1500-2-1.
Config/testthat/edition: 3
NeedsCompilation: yes
Packaged: 2023-09-11 08:10:03 UTC; Dominik Schulz
Author: Yuanhua Feng [aut] (Paderborn University, Germany),
  Sebastian Letmathe [aut] (Paderborn University, Germany),
  Dominik Schulz [aut, cre] (Paderborn University, Germany),
  Thomas Gries [ctb] (Paderborn University, Germany),
  Marlon Fritz [ctb] (Paderborn University, Germany)
Maintainer: Dominik Schulz <schulzd@mail.uni-paderborn.de>
Repository: CRAN
Date/Publication: 2023-09-11 08:50:02 UTC
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Archs: x64
