# Maximal Correlation and the Rate of Fisher Information Convergence in the Central Limit Theorem

@article{Johnson2020MaximalCA, title={Maximal Correlation and the Rate of Fisher Information Convergence in the Central Limit Theorem}, author={Oliver Johnson}, journal={IEEE Transactions on Information Theory}, year={2020}, volume={66}, pages={4992-5002} }

We consider the behaviour of the Fisher information of scaled sums of independent and identically distributed random variables in the Central Limit Theorem regime. We show how this behaviour can be related to the second-largest non-trivial eigenvalue of the operator associated with the Hirschfeld–Gebelein–Rényi maximal correlation. We prove that assuming this eigenvalue satisfies a strict inequality, an <inline-formula> <tex-math notation="LaTeX">$O(1/n)$ </tex-math></inline-formula> rate of…

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