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). .


Reference manual

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install.packages("TSdeeplearning")

1.0.1 by Ronit Jaiswal, 6 months ago


Browse source code at https://github.com/cran/TSdeeplearning


Authors: Ronit Jaiswal [aut, cre] , Girish Kumar Jha [aut, ths, ctb] , Rajeev Ranjan Kumar [aut, ctb] , Kapil Choudhary [aut, ctb]


Documentation:   PDF Manual  


GPL-3 license


Imports tensorflow, keras, reticulate, tsutils, BiocGenerics, utils, graphics, magrittr


Imported by EEMDlstm.


See at CRAN