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The nonparametric trend and its derivatives in equidistant time series (TS) with long-memory 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. The smoothing methods of the package are described in Letmathe, S., Beran, J. and Feng, Y., (2023) <doi:10.1080/03610926.2023.2276049>.
| Version: | 2.0.1 |
| Depends: | R (≥ 2.10) |
| Imports: | fracdiff, stats, utils, smoots, graphics, grDevices, Rcpp, future, furrr, ggplot2 |
| LinkingTo: | Rcpp, RcppArmadillo |
| Published: | 2024-05-07 |
| DOI: | 10.32614/CRAN.package.esemifar |
| Author: | Yuanhua Feng [aut] (Paderborn University, Germany), Jan Beran [aut] (University of Konstanz, Germany), Sebastian Letmathe [aut] (Paderborn University, Germany), Dominik Schulz [aut, cre] (Paderborn University, Germany) |
| Maintainer: | Dominik Schulz <dominik.schulz at uni-paderborn.de> |
| License: | GPL-3 |
| URL: | https://wiwi.uni-paderborn.de/en/dep4/feng/ |
| NeedsCompilation: | yes |
| Materials: | README NEWS |
| In views: | TimeSeries |
| CRAN checks: | esemifar results |
| Reference manual: | esemifar.pdf |
| Package source: | esemifar_2.0.1.tar.gz |
| Windows binaries: | r-devel: esemifar_2.0.1.zip, r-release: esemifar_2.0.1.zip, r-oldrel: esemifar_2.0.1.zip |
| macOS binaries: | r-release (arm64): esemifar_2.0.1.tgz, r-oldrel (arm64): esemifar_2.0.1.tgz, r-release (x86_64): esemifar_2.0.1.tgz, r-oldrel (x86_64): esemifar_2.0.1.tgz |
| Old sources: | esemifar archive |
| Reverse imports: | ufRisk |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.