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TSdeeplearning: Deep Learning Model for Time Series Forecasting

Provides deep learning models for time series forecasting using Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). These models capture temporal dependencies and address vanishing gradient issues in sequential data. The package enables efficient forecasting for univariate time series. For methodological details see Jaiswal and co-authors (2022). <doi:10.1007/s00521-021-06621-3>.

Version: 1.0.1
Depends: R (≥ 2.10)
Imports: tensorflow, keras, reticulate, tsutils, BiocGenerics, utils, graphics, magrittr
Published: 2026-04-13
DOI: 10.32614/CRAN.package.TSdeeplearning
Author: Ronit Jaiswal [aut, cre], Girish Kumar Jha [aut, ths, ctb], Rajeev Ranjan Kumar [aut, ctb], Kapil Choudhary [aut, ctb]
Maintainer: Ronit Jaiswal <ronitjaiswal2912 at gmail.com>
License: GPL-3
NeedsCompilation: no
Language: en-US
CRAN checks: TSdeeplearning results

Documentation:

Reference manual: TSdeeplearning.html , TSdeeplearning.pdf

Downloads:

Package source: TSdeeplearning_1.0.1.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available
Old sources: TSdeeplearning archive

Linking:

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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.
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