Wide-Sense Stationarity Test Based on Geometric Structure of Covariance
Published:Dec 29, 2025 07:19
•1 min read
•ArXiv
Analysis
This article likely presents a novel statistical test for wide-sense stationarity, a property of time series data. The approach leverages the geometric properties of the covariance matrix, which captures the relationships between data points at different time lags. This suggests a potentially more efficient or insightful method for determining if a time series is stationary compared to traditional tests. The source, ArXiv, indicates this is a pre-print, meaning it's likely undergoing peer review or is newly published.
Key Takeaways
- •Focuses on a statistical test for wide-sense stationarity.
- •Utilizes the geometric structure of the covariance matrix.
- •Potentially offers a new or improved method for stationarity testing.
- •Published on ArXiv, indicating it's likely a research paper.
Reference
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