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arXiv · 2409.06437

A Short Information-Theoretic Analysis of Linear Auto-Regressive Learning

Ingvar Ziemann
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Abstract

In this note, we give a short information-theoretic proof of the consistency of the Gaussian maximum likelihood estimator in linear auto-regressive models. Our proof yields nearly optimal non-asymptotic rates for parameter recovery and works without any invocation of stability in the case of finite hypothesis classes.

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Ingvar Ziemann. 2024-09-10. A Short Information-Theoretic Analysis of Linear Auto-Regressive Learning. https://arxiv.org/abs/2409.06437

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