esemifar: Smoothing Long-Memory Time Series
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 |
Documentation:
Downloads:
Reverse dependencies:
Linking:
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