Method and tool for generating time series forecasts using an ensemble wavelet-based auto-regressive neural network architecture. This method provides additional support of exogenous variables and also generates confidence interval. This package provides EWNet model for time series forecasting based on the algorithm by Panja, et al. (2022) and Panja, et al. (2023) <doi:10.48550/arXiv.2206.10696> <doi:10.1016/j.chaos.2023.113124>.
| Version: | 0.1.0 |
| Depends: | datasets |
| Imports: | forecast, Metrics, stats, wavelets |
| Suggests: | ggplot2 |
| Published: | 2023-03-22 |
| DOI: | 10.32614/CRAN.package.epicasting |
| Author: | Madhurima Panja [aut], Tanujit Chakraborty [aut, cre, cph] |
| Maintainer: | Tanujit Chakraborty <tanujitisi at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| In views: | Epidemiology |
| CRAN checks: | epicasting results |
| Reference manual: | epicasting.html , epicasting.pdf |
| Package source: | epicasting_0.1.0.tar.gz |
| Windows binaries: | r-devel: epicasting_0.1.0.zip, r-release: epicasting_0.1.0.zip, r-oldrel: epicasting_0.1.0.zip |
| macOS binaries: | r-release (arm64): epicasting_0.1.0.tgz, r-oldrel (arm64): epicasting_0.1.0.tgz, r-release (x86_64): epicasting_0.1.0.tgz, r-oldrel (x86_64): epicasting_0.1.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=epicasting to link to this page.
Need a high-speed mirror for your open-source project?
Contact our mirror admin team at info@clientvps.com.
This archive is provided as a free public service to the community.
Proudly supported by infrastructure from VPSPulse , RxServers , BuyNumber , UnitVPS , OffshoreName and secure payment technology by ArionPay.