CRAN/E | DCSmooth

DCSmooth

Nonparametric Regression and Bandwidth Selection for Spatial Models

Installation

About

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) , Schaefer/Feng (2021) .

Key Metrics

Version 1.1.2
R ≥ 3.1.0
Published 2021-10-21 909 days ago
Needs compilation? yes
License GPL-3
CRAN checks DCSmooth results

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Maintainer

Maintainer

Bastian Schaefer

bastian.schaefer@uni-paderborn.de

Authors

Bastian Schaefer

aut / cre

Sebastian Letmathe

ctb

Yuanhua Feng

ths

Material

README
NEWS
Reference manual
Package source

Vignettes

DCSmooth

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

DCSmooth archive

Depends

R ≥ 3.1.0

Imports

doParallel
foreach
fracdiff
parallel
plotly
Rcpp
stats

Suggests

knitr
rmarkdown
testthat

LinkingTo

Rcpp
RcppArmadillo