Package: smoots
Type: Package
Title: Nonparametric Estimation of the Trend and Its Derivatives in TS
Version: 1.0.1
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.
    The methods of the package are described in
    Feng, Y., and Gries, T., (2017) <http://groups.uni-paderborn.de/wp-wiwi/RePEc/pdf/ciepap/WP102.pdf>. 
    A current version of the paper that is also referred to in the 
    documentation of the functions is prepared for publication.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.1
Imports: stats, graphics
Suggests: knitr, rmarkdown, fGarch
Depends: R (>= 2.10)
Authors@R: c(
  person("Yuanhua", "Feng", role = "aut", 
    comment = "Paderborn University, Germany"),
  person("Dominik", "Schulz", role = c("aut", "cre"), 
    email = "schulzd@mail.uni-paderborn.de",
    comment = "Paderborn University, Germany"),
  person("Thomas", "Gries", role = "ctb",
    comment = "Paderborn University, Germany"),
  person("Marlon", "Fritz", role = "ctb",
    comment = "Paderborn University, Germany"),
  person("Sebastian", "Letmathe", role = "ctb",
    comment = "Paderborn University, Germany"))         
URL: https://wiwi.uni-paderborn.de/en/dep4/feng/
        https://wiwi.uni-paderborn.de/dep4/gries/
NeedsCompilation: no
Packaged: 2019-12-02 13:23:38 UTC; schulzd
Author: Yuanhua Feng [aut] (Paderborn University, Germany),
  Dominik Schulz [aut, cre] (Paderborn University, Germany),
  Thomas Gries [ctb] (Paderborn University, Germany),
  Marlon Fritz [ctb] (Paderborn University, Germany),
  Sebastian Letmathe [ctb] (Paderborn University, Germany)
Maintainer: Dominik Schulz <schulzd@mail.uni-paderborn.de>
Repository: CRAN
Date/Publication: 2019-12-02 15:40:02 UTC
