Javascript bindings to the augurs
time series framework.
- Add the package to your dependencies:
"dependencies": {
"@bsull/augurs": "^0.1.0"
}
- Import the default function and initialize once somewhere in your application:
import init from "@bsull/augurs";
init().then(() => console.log("Initialized augurs"));
- Use the various ETS, changepoint, outlier, or seasonality detection algorithms. For example:
import { ets, seasonalities } from "@bsull/augurs"
const y = new Float64Array([1.0, 2.0, 3.0, 1.0, 2.0, 3.0]); // your time series data
const seasonLengths = seasonalities(y);
const model = ets(seasonLengths, { impute: true });
model.fit(y);
const predictionInterval = 0.95;
// Generate in-sample predictions for the training set.
const { point, lower, upper } = model.predictInSample(predictionInterval);
// Generate out-of-sample forecasts.
const { point: futurePoint, lower: futureLower, upper: futureUpper } = model.predict(10, predictionInterval);