TDSTNN: Time Delay Spatio Temporal Neural Network
STARMA (Space-Time Autoregressive Moving Average) models are commonly utilized in modeling and forecasting spatiotemporal time series data. However, the intricate nonlinear dynamics observed in many space-time rainfall patterns often exceed the capabilities of conventional STARMA models. This R package enables the fitting of Time Delay Spatio-Temporal Neural Networks, which are adept at handling such complex nonlinear dynamics efficiently. For detailed methodology, please refer to Saha et al. (2020) <doi:10.1007/s00704-020-03374-2>.
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.2.3), nnet |
| Published: |
2024-05-26 |
| DOI: |
10.32614/CRAN.package.TDSTNN |
| Author: |
Mrinmoy Ray [aut, cre],
Rajeev Ranjan Kumar [aut, ctb],
Kanchan Sinha [aut, ctb],
K. N. Singh [aut, ctb] |
| Maintainer: |
Mrinmoy Ray <mrinmoy4848 at gmail.com> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| CRAN checks: |
TDSTNN results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=TDSTNN
to link to this page.