Crate augurs_ets
source ·Expand description
Exponential smoothing models.
This crate provides exponential smoothing models for time series forecasting. The models are implemented in Rust and are based on the statsforecast Python package.
Important: This crate is still in development and the API is subject to change. Seasonal models are not yet implemented, and some model types have not been tested.
§Example
use augurs_core::prelude::*;
use augurs_ets::AutoETS;
let data: Vec<_> = (0..10).map(|x| x as f64).collect();
let mut search = AutoETS::new(1, "ZZN")
.expect("ZZN is a valid model search specification string");
let model = search.fit(&data).expect("fit should succeed");
let forecast = model.predict(5, 0.95).expect("predict should succeed");
assert_eq!(forecast.point.len(), 5);
assert_eq!(forecast.point, vec![10.0, 11.0, 12.0, 13.0, 14.0]);
Modules§
- Data for testing and examples.
- A single model of the ETS family.
Structs§
- Automatic ETS model selection.
- Auto model search specification.
- A fitted
AutoETS
model.
Enums§
- Errors returned by this crate.