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) <>. A current version of the paper that is also referred to in the documentation of the functions is prepared for publication.


Reference manual

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1.0.1 by Dominik Schulz, a year ago

Browse source code at

Authors: 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)

Documentation:   PDF Manual  

Task views: Time Series Analysis

GPL-3 license

Imports stats, graphics

Suggests knitr, rmarkdown, fGarch

See at CRAN