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DCSmooth  

Nonparametric Regression and Bandwidth Selection for Spatial Models
View on CRAN: Click here


Download and install DCSmooth package within the R console
Install from CRAN:
install.packages("DCSmooth")

Install from Github:
library("remotes")
install_github("cran/DCSmooth")

Install by package version:
library("remotes")
install_version("DCSmooth", "1.1.2")



Attach the package and use:
library("DCSmooth")
Maintained by
Bastian Schaefer
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-08-12
Latest Update: 2021-10-21
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) , Schaefer/Feng (2021) .
How to cite:
Bastian Schaefer (2021). DCSmooth: Nonparametric Regression and Bandwidth Selection for Spatial Models. R package version 1.1.2, https://cran.r-project.org/web/packages/DCSmooth. Accessed 05 Jun. 2026.
Previous versions and publish date:
1.0.1 (2021-08-12 11:10), 1.0.2 (2021-08-25 14:50), 1.1.2 (2021-10-21 17:20)
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Complete documentation for DCSmooth
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