tsfngm
0.1.0Time Series Forecasting using Nonlinear Growth Models
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Overview
About
Nonlinear growth models are extremely useful in gaining insight into the underlying mechanism. These models are generally 'mechanistic,' with parameters that have biological meaning. This package allows you to fit and forecast time series data using nonlinear growth models.
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- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
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Dependencies
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Depends (2)
R >= 2.6stats
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Code & Tests
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Contributors (4)
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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
- 2021-09-23
- Total releases
- 1 / 5 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 2.6
- Download size
- 2.6 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet