Identifiability of parametric random matrix models

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Tomohiro Hayase

Published: 13 Jan 2020, Last Modified: 12 May 2025Infinite Dimensional Analysis, Quantum Probability and Related Topics, VOL. 22, NO. 03.EveryoneCC BY 4.0
Abstract: We investigate parameter identifiability of spectral distributions of random matrices. In particular, we treat compound Wishart type and signal-plus-noise type. We show that each model is identifiable up to some kind of rotation of parameter space. Our method is based on free probability theory.