Introduction

augurs is a Rust library for time series analysis and forecasting. It provides a comprehensive set of tools for working with time series data, including:

• Forecasting with multiple algorithms including ETS, MSTL, and Prophet
• Outlier detection using MAD and DBSCAN
• Time series clustering with DTW distance metrics
• Seasonality and changepoint detection
• Data preprocessing and transformation tools

Built with a focus on performance and ease of use, augurs offers both high-level APIs for common tasks and low-level components for custom implementations. The library supports Python and JavaScript bindings, making it accessible across different programming environments.

Whether you're building a production forecasting system or analyzing seasonal patterns in data, augurs provides the tools you need for robust time series analysis.

These docs are a work-in-progress; the missing pages will hopefully be added soon.