swMATH ID: 35248
Software Authors: Yuanhua Feng, Dominik Schulz, Thomas Gries, Marlon Fritz, Sebastian Letmathe
Description: R package smoots: Nonparametric Estimation of the Trend and Its Derivatives in TS. 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.
Homepage: https://cran.r-project.org/web/packages/smoots/index.html
Dependencies: R
Keywords: bandwidth selection; dependent errors; derivative estimation; spectral density; semiparametric modelling; implementation in R
Related Software: R
Cited in: 1 Publication

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