Daniel J McDonald, Cosma Rohilla Shalizi, Mark Schervish
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引用次数: 0
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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