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The best ANN structure for time series data analysis is a demanding need in the present era. This package will find the best-fitted ANN model based on forecasting accuracy. The optimum size of the hidden layers was also determined after determining the number of lags to be included. This package has been developed using the algorithm of Paul and Garai (2021) <doi:10.1007/s00500-021-06087-4>.
| Version: | 0.1.0 |
| Imports: | forecast, gtools, stats, utils |
| Published: | 2021-12-14 |
| Author: | Md Yeasin [aut, cre], Ranjit Kumar Paul [aut], Dipro Sinha [aut] |
| Maintainer: | Md Yeasin <yeasin.iasri at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| In views: | TimeSeries |
| CRAN checks: | TSANN results |
| Reference manual: | TSANN.pdf |
| Package source: | TSANN_0.1.0.tar.gz |
| Windows binaries: | r-devel: TSANN_0.1.0.zip, r-release: TSANN_0.1.0.zip, r-oldrel: TSANN_0.1.0.zip |
| macOS binaries: | r-release (arm64): TSANN_0.1.0.tgz, r-oldrel (arm64): TSANN_0.1.0.tgz, r-release (x86_64): TSANN_0.1.0.tgz, r-oldrel (x86_64): TSANN_0.1.0.tgz |
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These binaries (installable software) and packages are in development.
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