Discussion critiques robust independent component analysis techniques, highlighting implications and performance metrics.
Plain Language In this discussion, we comment on the paper by Leyder et al., which introduces a new framework for robust independent component analysis based on robust distance correlation. Our discussion focuses on the role of whitening, the choice of scatter matrices, and the implications of the independence property in robust ICA. We further argue that the minimum distance index is preferable to the Amari index as a performance measure, as it admits a direct connection to the limiting distribution of ICA estimators. Overall, the paper by Leyder et al. constitutes an important contribution to robust blind source separation and opens several promising avenues for future research.
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Nordhausen et al. (2026) studied this question.
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