Package: esemifar
Type: Package
Title: Smoothing Long-Memory Time Series
Version: 2.0.1
Description: The nonparametric trend and its derivatives in equidistant time 
    series (TS) with long-memory 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.
    The smoothing methods of the package are described in Letmathe, S., Beran,
    J. and Feng, Y., (2023) <doi:10.1080/03610926.2023.2276049>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: fracdiff, stats, utils, smoots, graphics, grDevices, Rcpp,
        future, furrr, ggplot2
Depends: R (>= 2.10)
LinkingTo: Rcpp, RcppArmadillo
Authors@R: 
  c(person("Yuanhua", "Feng", role = "aut", 
    comment = "Paderborn University, Germany"),
    person("Jan", "Beran", role = "aut", 
    comment = "University of Konstanz, Germany"),
  person("Sebastian", "Letmathe", role = c("aut"),
    comment = "Paderborn University, Germany"),
  person("Dominik", "Schulz", role = c("aut", "cre"), 
    email = "dominik.schulz@uni-paderborn.de",
    comment = "Paderborn University, Germany"))
URL: https://wiwi.uni-paderborn.de/en/dep4/feng/
Acknowledgments: This work was supported by the German DFG project
        GZ-FE-1500-2-1.
RoxygenNote: 7.2.3
NeedsCompilation: yes
Packaged: 2024-05-07 10:12:01 UTC; Dominik Schulz
Author: Yuanhua Feng [aut] (Paderborn University, Germany),
  Jan Beran [aut] (University of Konstanz, Germany),
  Sebastian Letmathe [aut] (Paderborn University, Germany),
  Dominik Schulz [aut, cre] (Paderborn University, Germany)
Maintainer: Dominik Schulz <dominik.schulz@uni-paderborn.de>
Repository: CRAN
Date/Publication: 2024-05-07 10:40:03 UTC
Built: R 4.2.3; aarch64-apple-darwin20; 2024-05-10 02:26:38 UTC; unix
Archs: esemifar.so.dSYM
