chotanansub/autotrend
Adaptive local linear trend decomposition for time series analysis.
This tool helps financial analysts, operations managers, or data scientists understand the underlying trend in their time series data, like stock prices or sensor readings. You provide a sequence of numbers over time, and it outputs a clear breakdown of the stable linear segments that make up the overall trend. It's designed for anyone needing to efficiently identify shifts and patterns in historical data.
Available on PyPI.
Use this if you need to quickly and adaptively find the long-term trends in your time series without manually defining change points or fitting complex models at every data point.
Not ideal if your primary goal is forecasting future values or if your time series contains strong, complex seasonal patterns that need to be explicitly modeled.
Stars
8
Forks
—
Language
Python
License
MIT
Category
Last pushed
Feb 02, 2026
Commits (30d)
0
Dependencies
5
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