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Describes a series first. After that does time series analysis using one hybrid model and two specially structured Machine Learning (ML) (Artificial Neural Network or ANN and Support Vector Regression or SVR) models. More information can be obtained from Paul and Garai (2022) <doi:10.1007/s41096-022-00128-3>.
Version: | 0.1.0 |
Imports: | AllMetrics, DescribeDF, stats, dplyr, psych, FinTS, tseries, forecast, fGarch, aTSA, neuralnet, e1071 |
Published: | 2023-04-13 |
DOI: | 10.32614/CRAN.package.AriGaMyANNSVR |
Author: | Mr. Sandip Garai [aut, cre] |
Maintainer: | Mr. Sandip Garai <sandipnicksandy at gmail.com> |
License: | GPL-3 |
NeedsCompilation: | no |
CRAN checks: | AriGaMyANNSVR results |
Reference manual: | AriGaMyANNSVR.pdf |
Package source: | AriGaMyANNSVR_0.1.0.tar.gz |
Windows binaries: | r-devel: AriGaMyANNSVR_0.1.0.zip, r-release: AriGaMyANNSVR_0.1.0.zip, r-oldrel: AriGaMyANNSVR_0.1.0.zip |
macOS binaries: | r-release (arm64): AriGaMyANNSVR_0.1.0.tgz, r-oldrel (arm64): AriGaMyANNSVR_0.1.0.tgz, r-release (x86_64): AriGaMyANNSVR_0.1.0.tgz, r-oldrel (x86_64): AriGaMyANNSVR_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.