Discussion examines robust ICA through bowl transform geometry and consistency for dimensional analysis, implying stronger performance in complex data.
This is a discussion of PICARD, the robust independent component analysis (ICA) estimator built on a transformed distance correlation and on the bowl transform.I develop two threads.The first reads the bowl transform as a multivariate redescending ψ-function, makes its exponential decay explicit, and describes how the transformed norm concentrates as the dimension grows.The second examines the reach of the strong-consistency result, relating its population target to classical ICA identifiability and to the behavior of robust whitening under non-elliptical sources.
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Pietro Coretto (2026) studied this question.
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