tsfngm
Time Series Forecasting using Nonlinear Growth Models
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | tsfngm_0.1.0.tar.gz |
14.2 KiB |
0.1.0 |
rolling linux/noble R-4.5 | tsfngm_0.1.0.tar.gz |
14.1 KiB |
0.1.0 |
rolling source/ R- | tsfngm_0.1.0.tar.gz |
2.5 KiB |
0.1.0 |
latest linux/jammy R-4.5 | tsfngm_0.1.0.tar.gz |
14.2 KiB |
0.1.0 |
latest linux/noble R-4.5 | tsfngm_0.1.0.tar.gz |
14.1 KiB |
0.1.0 |
latest source/ R- | tsfngm_0.1.0.tar.gz |
2.5 KiB |
0.1.0 |
2026-04-26 source/ R- | tsfngm_0.1.0.tar.gz |
2.5 KiB |
0.1.0 |
2026-04-23 source/ R- | tsfngm_0.1.0.tar.gz |
2.5 KiB |
0.1.0 |
2026-04-09 windows/windows R-4.5 | tsfngm_0.1.0.zip |
16.8 KiB |
0.1.0 |
2025-04-20 source/ R- | tsfngm_0.1.0.tar.gz |
2.5 KiB |