Identifiability of parametric random matrix models

12/27/2018

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by   Tomohiro Hayase, et al.

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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.