Estimating $β$-mixing coefficients

Statistics – Machine Learning

Scientific paper

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9 pages, accepted by AIStats. CMU Statistics Technical Report

Scientific paper

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, nor are there 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 $L_1$-risk consistent.

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