A small Java library for time-series analysis and forecasting.

• exponential smoothing: single, double, and triple
• moving averages: simple, cumulative, exponential, and weighted
• transformations: log, roots, and Box-Cox
• statistics: mean, variance, autocovariance, ACF, and PACF
• stationarity testing with Augmented Dickey-Fuller

The project targets Java 17 and uses Gradle.

gradle test

This snapshot does not include the generated gradle-wrapper.jar, so gradle is the most reliable entry point unless you regenerate the wrapper locally.

Primary implementation packages:

• tslib.collect
• tslib.model.expsmoothing
• tslib.movingaverage
• tslib.tests
• tslib.transform
• tslib.util

Compatibility aliases added in this patch:

• tslib.model.* forwards to tslib.model.expsmoothing.*
• tslib.stats.Stats forwards to tslib.util.Stats

These aliases make the public API line up with the README examples without breaking existing imports.

import java.util.List; import tslib.model.ExponentialSmoothing; import tslib.model.TripleExpSmoothing; import tslib.movingaverage.MovingAverage; import tslib.movingaverage.SimpleMovingAverage; import tslib.transform.Transform; import tslib.util.Util; List<Double> data = Util.readFile("data/hotel.txt"); ExponentialSmoothing model = new TripleExpSmoothing(0.5, 0.3, 0.2, 12, false); List<Double> forecast = model.forecast(data, 5); MovingAverage sma = new SimpleMovingAverage(3); List<Double> smoothed = sma.compute(data); double lambda = Transform.boxCoxLambdaSearch(data); List<Double> transformed = Transform.boxCox(data, lambda);

See the examples/ directory for runnable snippets.

This patch makes the following repo-level improvements:

• fixes the Gradle project name from expsmoothing to tslib
• removes deprecated jcenter() in favor of mavenCentral()
• adds API compatibility aliases for the package names shown in the docs
• refreshes CI to use current Gradle and Java setup
• adds focused regression tests and example programs
• adds a changelog stub for future releases