Package: DCSmooth
Type: Package
Title: Nonparametric Regression and Bandwidth Selection for Spatial
        Models
Version: 1.0.1
Authors@R: c(person("Bastian", "Schaefer",
    email = "bastian.schaefer@uni-paderborn.de", role = c("aut", "cre")),
    person("Sebastian", "Letmathe", role = "ctb"), person("Yuanhua", "Feng", 
    role = "ctb"))
Description: Nonparametric smoothing techniques for
    data on a lattice and functional time series. Smoothing is done via
    kernel regression or local polynomial regression, a bandwidth selection
    procedure based on an iterative plug-in algorithm is implemented. This
    package allows for modeling a dependency structure of the error terms
    of the nonparametric regression model.
    Methods used in this paper are described in
    Beran/Feng (2002) <doi:10.1198/106186002420>,
    Mueller/Wang (1994) <doi:10.2307/2533197>,
    Feng/Schaefer (2021) <https://ideas.repec.org/p/pdn/ciepap/144.html>, 
    Schaefer/Feng (2021) <https://ideas.repec.org/p/pdn/ciepap/143.html>.
Author: Bastian Schaefer [aut, cre],
  Sebastian Letmathe [ctb],
  Yuanhua Feng [ctb]
Maintainer: Bastian Schaefer <bastian.schaefer@uni-paderborn.de>
License: GPL-3
LazyData: true
Imports: Rcpp, plotly, fracdiff, stats
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.1.1
Encoding: UTF-8
VignetteBuilder: knitr
Depends: R (>= 3.1.0)
Suggests: knitr, rmarkdown, testthat
NeedsCompilation: yes
Packaged: 2021-08-10 09:26:26 UTC; Bastian Schäfer
Repository: CRAN
Date/Publication: 2021-08-12 09:10:06 UTC
