DCSmooth
Nonparametric Regression and Bandwidth Selection for Spatial Models
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.
- Version1.1.2
- R version≥ 3.1.0
- LicenseGPL-3
- Needs compilation?Yes
- Last release10/21/2021
Documentation
Team
Bastian Schaefer
Sebastian Letmathe
Show author detailsRolesContributorYuanhua Feng
Show author detailsRolesThesis advisor
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- Imports5 packages
- Suggests3 packages
- Linking To2 packages