DCSmooth-package: Nonparametric Regression and Bandwidth Selection for Spatial...

In DCSmooth: Nonparametric Regression and Bandwidth Selection for Spatial Models

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>.

Package Content

Index: This package was not yet installed at build time.

Maintainer

Bastian Schaefer <[e-mail]>

Author(s)

Bastian Schaefer [aut, cre], Sebastian Letmathe [ctb], Yuanhua Feng [ths]

DCSmooth documentation built on Oct. 21, 2021, 5:07 p.m.