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Testing, Implementation, and Forecasting of the ARIMA-ANN hybrid model. The ARIMA-ANN hybrid model combines the distinct strengths of the Auto-Regressive Integrated Moving Average (ARIMA) model and the Artificial Neural Network (ANN) model for time series forecasting.For method details see Zhang, GP (2003) <doi:10.1016/S0925-2312(01)00702-0>.
| Version: | 0.1.0 |
| Depends: | R (≥ 2.3.1), stats, forecast, tseries |
| Published: | 2022-10-13 |
| DOI: | 10.32614/CRAN.package.ARIMAANN |
| Author: | Ramasubramanian V. [aut, ctb], Mrinmoy Ray [aut, cre] |
| Maintainer: | Mrinmoy Ray <mrinmoy4848 at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | ARIMAANN results |
| Reference manual: | ARIMAANN.pdf |
| Package source: | ARIMAANN_0.1.0.tar.gz |
| Windows binaries: | r-devel: ARIMAANN_0.1.0.zip, r-release: ARIMAANN_0.1.0.zip, r-oldrel: ARIMAANN_0.1.0.zip |
| macOS binaries: | r-release (arm64): ARIMAANN_0.1.0.tgz, r-oldrel (arm64): ARIMAANN_0.1.0.tgz, r-release (x86_64): ARIMAANN_0.1.0.tgz, r-oldrel (x86_64): ARIMAANN_0.1.0.tgz |
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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.