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Updated: Apr 5, 2026

Quantifying Mixing using Magnetic Resonance Imaging
Published on: January 25, 2012
Estimating beta-mixing coefficients
Daniel J McDonald1, Cosma Rohilla Shalizi2, Mark Schervish3
1Department of Statististics, Carnegie Mellon University, Pittsburgh, PA 15213, danielmc@stat.cmu.edu.
Abstract:
The literature on statistical learning for time series assumes the asymptotic independence or "mixing" of the data-generating process. These mixing assumptions are never tested, and there are no methods for estimating mixing rates from data. We give an estimator for the beta-mixing rate based on a single stationary sample path and show it is L1-risk consistent.
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