The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
ETS stands for Error, Trend, and Seasonality, and it is a popular time series forecasting method. Wavelet decomposition can be used for denoising, compression, and feature extraction of signals. By removing the high-frequency components, wavelet decomposition can remove noise from the data while preserving important features. A hybrid Wavelet ETS (Error Trend-Seasonality) model has been developed for time series forecasting using algorithm of Anjoy and Paul (2017) <doi:10.1007/s00521-017-3289-9>.
| Version: | 0.1.0 |
| Imports: | dplyr, Metrics, tseries, stats, wavelets, forecast, caretForecast |
| Published: | 2023-04-05 |
| DOI: | 10.32614/CRAN.package.WaveletETS |
| Author: | Dr. Ranjit Kumar Paul [aut], Dr. Md Yeasin [aut, cre] |
| Maintainer: | Dr. Md Yeasin <yeasin.iasri at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | WaveletETS results |
| Reference manual: | WaveletETS.pdf |
| Package source: | WaveletETS_0.1.0.tar.gz |
| Windows binaries: | r-devel: WaveletETS_0.1.0.zip, r-release: WaveletETS_0.1.0.zip, r-oldrel: WaveletETS_0.1.0.zip |
| macOS binaries: | r-release (arm64): WaveletETS_0.1.0.tgz, r-oldrel (arm64): WaveletETS_0.1.0.tgz, r-release (x86_64): WaveletETS_0.1.0.tgz, r-oldrel (x86_64): WaveletETS_0.1.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=WaveletETS to link to this page.
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.