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On positive definite thresholding of correlation matrices
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On positive definite thresholding of correlation matrices

Sujit Sakharam Damase and James Eldred Pascoe
ArXiv.org
11 Mar 2026
url
https://doi.org/10.48550/arxiv.2603.11040View
Preprint (Author's original)arXiv.org - Non-exclusive license to distribute Open

Abstract

Computer Science - Information Theory Mathematics - Classical Analysis and ODEs Mathematics - Functional Analysis Mathematics - Information Theory Mathematics - Metric Geometry Mathematics - Statistics Theory Statistics - Theory
Standard thresholding techniques for correlation matrices often destroy positive semidefiniteness. We investigate the construction of positive definite functions that vanish on specific setsK βŠ† [-1,1) , ensuring that the thresholded matrix remains a valid correlation matrix. We establish existence results, define a criterion for faithfulness based on the linear coefficient of the normalized Gegenbauer expansion in analogy with Delsarte's method in coding theory, and provide bounds for thresholding at single points and pairs of points. We prove that for correlation matrices of rankn , any soft-thresholding operator that preserves positive semidefiniteness necessarily induces a geometric collapse of the feature space, as quantified by anπ“ž(1/n)bound on the faithfulness constant. Such demonstrates that geometrically unbiased soft-thresholding limits the recoverable signal.

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