EMDSSAForecast: Hybrid EMD-SSA Forecasting with Artificial Neural Networks for Time Series

Implements a hybrid empirical mode decomposition, singular spectrum analysis, and artificial neural network forecasting framework for time series data. The framework extracts the trend from the first intrinsic mode function using singular spectrum analysis, forecasts the extracted trend and remaining decomposition components using artificial neural networks, and combines the component forecasts to obtain the final forecast. For methodological details, refer to Kumar et al. (2026) <doi:10.1007/s10791-026-10076-2>.

Version:	0.1.0
Imports:	Rlibeemd, Rssa, neuralnet
Suggests:	spelling, testthat (≥ 3.0.0)
Published:	2026-10-15
DOI:	10.32614/CRAN.package.EMDSSAForecast
Author:	Prabhat Kumar [aut, cre], Girish Kumar Jha [aut], Rajeev Ranjan Kumar [aut], Santosha Rathod [aut], R N Singh [aut]
Maintainer:	Prabhat Kumar <prabhatkkv at gmail.com>
License:	MIT + file LICENSE
NeedsCompilation:	no
Language:	en-US
CRAN checks:	EMDSSAForecast results

Documentation:

Reference manual:

EMDSSAForecast.html , EMDSSAForecast.pdf

Downloads:

Package source:	EMDSSAForecast_0.1.0.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: EMDSSAForecast_0.1.0.zip
macOS binaries:	r-release (arm64): EMDSSAForecast_0.1.0.tgz, r-oldrel (arm64): EMDSSAForecast_0.1.0.tgz, r-release (x86_64): EMDSSAForecast_0.1.0.tgz, r-oldrel (x86_64): EMDSSAForecast_0.1.0.tgz

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