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This is a Quantitative Study study.

October 19, 2025Open Access

Edgeworth corrections for the spiked eigenvalues of non-Gaussian sample covariance matrices with applications

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Edgeworth expansions for spiked eigenvalues in non-Gaussian data significantly enhance confidence interval accuracy.
Simulation studies show the proposed methodology outperforms existing methods in low-dimensional cases.
The new estimator effectively identifies the number of spikes in various scenarios.
This study addresses the previously unsolved extension of Edgeworth corrections beyond Gaussian observations.

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This research establishes Edgeworth expansions for spiked eigenvalues in non-Gaussian settings, highlighting improvements in robustness and accuracy.

Wei et al. (2025) studied this question.

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This research establishes Edgeworth expansions for spiked eigenvalues in non-Gaussian settings, highlighting improvements in robustness and accuracy.