Type: Package
Package: DCSmooth
Title: Nonparametric Regression and Bandwidth Selection for Spatial
        Models
Version: 1.1.2
Authors@R: c(
    person("Bastian", "Schaefer", , "bastian.schaefer@uni-paderborn.de", role = c("aut", "cre")),
    person("Sebastian", "Letmathe", role = "ctb"),
    person("Yuanhua Feng", role = "ths")
  )
Author: Bastian Schaefer [aut, cre],
  Sebastian Letmathe [ctb],
  Yuanhua Feng [ths]
Maintainer: Bastian Schaefer <bastian.schaefer@uni-paderborn.de>
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 Feng/Schaefer (2021)
    <https://ideas.repec.org/p/pdn/ciepap/144.html>, Schaefer/Feng (2021)
    <https://ideas.repec.org/p/pdn/ciepap/143.html>.
License: GPL-3
Depends: R (>= 3.1.0)
Imports: doParallel, foreach, fracdiff, parallel, plotly, Rcpp, stats
Suggests: knitr, rmarkdown, testthat
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.2
NeedsCompilation: yes
Packaged: 2021-10-21 14:58:07 UTC; Bastian Schäfer
Repository: CRAN
Date/Publication: 2021-10-21 15:20:08 UTC
Built: R 4.2.3; x86_64-w64-mingw32; 2024-04-24 02:58:38 UTC; windows
ExperimentalWindowsRuntime: ucrt
Archs: x64
