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 |
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