fchamroukhi/SaMUraiS

StAtistical Models for the UnsupeRvised segmentAion of tIme-Series

20
/ 100
Experimental

This tool helps researchers, scientists, and data analysts find hidden patterns and changes within complex time-series data. You input a sequence of measurements or observations, and it automatically divides the data into distinct segments or 'regimes,' each with its own characteristic behavior. This is useful for understanding when and how the underlying process generating the data shifts, without needing prior knowledge of those changes.

No commits in the last 6 months.

Use this if you have univariate or multivariate time-series data and need to automatically identify different phases or operating conditions within it.

Not ideal if your data is not sequential or if you already know the exact points where changes in your data occur.

time-series analysis data segmentation pattern recognition statistical modeling regime detection
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 7 / 25

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Language

R

License

Last pushed

Jan 22, 2020

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