TDSTNN
0.1.0Time Delay Spatio Temporal Neural Network
0packages depend
1.6Kdownloads / year
–test coverage
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Overview
About
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.
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1NOTE12OK
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- NOTE r-devel-linux-x86_64-debian-gcc
Slowest check: 44 s · r-oldrel-windows-x86_64
Code health
None
Tests · ratio 0.00
not tracked
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1
Dependencies · direct
Check history
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
Documentation
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- Examples that run
- 100%
- Documented parameters
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- Return-value docs
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- References docs
- 100%
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Also on94 r2u3 autocran
Dependencies
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0 external dependencies (excludes base and recommended)
Depends (2)
R >= 4.2.3nnet
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none
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Code & Tests
People & History
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Contributors (3)
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Package Timeline
1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 0.1.0Latest2026-03-10 · current release
- RR 4.5.0 released · 2025-04-11
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Package metadata
- First published
- 2024-05-26
- Total releases
- 1 / 2 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 4.2.3
- Download size
- 2.2 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet