Nothing
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>.
Package details |
|
|---|---|
| Author | Ronit Jaiswal [aut, cre], Girish Kumar Jha [aut, ths, ctb], Rajeev Ranjan Kumar [aut, ctb], Kapil Choudhary [aut, ctb] |
| Maintainer | Ronit Jaiswal <ronitjaiswal2912@gmail.com> |
| License | GPL-3 |
| Version | 1.0.1 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.