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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>.
Version: | 1.1.2 |
Depends: | R (≥ 3.1.0) |
Imports: | doParallel, foreach, fracdiff, parallel, plotly, Rcpp, stats |
LinkingTo: | Rcpp, RcppArmadillo |
Suggests: | knitr, rmarkdown, testthat |
Published: | 2021-10-21 |
DOI: | 10.32614/CRAN.package.DCSmooth |
Author: | Bastian Schaefer [aut, cre], Sebastian Letmathe [ctb], Yuanhua Feng [ths] |
Maintainer: | Bastian Schaefer <bastian.schaefer at uni-paderborn.de> |
License: | GPL-3 |
NeedsCompilation: | yes |
Materials: | README NEWS |
CRAN checks: | DCSmooth results |
Reference manual: | DCSmooth.pdf |
Vignettes: |
DCSmooth |
Package source: | DCSmooth_1.1.2.tar.gz |
Windows binaries: | r-devel: DCSmooth_1.1.2.zip, r-release: DCSmooth_1.1.2.zip, r-oldrel: DCSmooth_1.1.2.zip |
macOS binaries: | r-release (arm64): DCSmooth_1.1.2.tgz, r-oldrel (arm64): DCSmooth_1.1.2.tgz, r-release (x86_64): DCSmooth_1.1.2.tgz, r-oldrel (x86_64): DCSmooth_1.1.2.tgz |
Old sources: | DCSmooth archive |
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