The nonparametric trend and its derivatives in equidistant time series (TS) with short-memory stationary errors can be estimated. The estimation is conducted via local polynomial regression using an automatically selected bandwidth obtained by a built-in iterative plug-in algorithm or a bandwidth fixed by the user. A Nadaraya-Watson kernel smoother is also built-in as a comparison. The methods of the package are described in Feng, Y., and Gries, T., (2017) <http://groups.uni-paderborn.de/wp-wiwi/RePEc/pdf/ciepap/WP102.pdf>. A current version of the paper that is also referred to in the documentation of the functions is prepared for publication.
| Version: | 1.0.1 |
| Depends: | R (≥ 2.10) |
| Imports: | stats, graphics |
| Suggests: | knitr, rmarkdown, fGarch |
| Published: | 2019-12-02 |
| Author: | Yuanhua Feng [aut] (Paderborn University, Germany), Dominik Schulz [aut, cre] (Paderborn University, Germany), Thomas Gries [ctb] (Paderborn University, Germany), Marlon Fritz [ctb] (Paderborn University, Germany), Sebastian Letmathe [ctb] (Paderborn University, Germany) |
| Maintainer: | Dominik Schulz <schulzd at mail.uni-paderborn.de> |
| License: | GPL-3 |
| URL: | https://wiwi.uni-paderborn.de/en/dep4/feng/ https://wiwi.uni-paderborn.de/dep4/gries/ |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| In views: | TimeSeries |
| CRAN checks: | smoots results |
| Reference manual: | smoots.pdf |
| Package source: | smoots_1.0.1.tar.gz |
| Windows binaries: | r-devel: smoots_1.0.1.zip, r-release: smoots_1.0.1.zip, r-oldrel: smoots_1.0.1.zip |
| macOS binaries: | r-release: smoots_1.0.1.tgz, r-oldrel: smoots_1.0.1.tgz |
| Old sources: | smoots archive |
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