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Computational limits to nonparametric estimation for ergodic processes (1002.1559v2)
Published 8 Feb 2010 in cs.IT and math.IT
Abstract: A new negative result for nonparametric estimation of binary ergodic processes is shown. I The problem of estimation of distribution with any degree of accuracy is studied. Then it is shown that for any countable class of estimators there is a zero-entropy binary ergodic process that is inconsistent with the class of estimators. Our result is different from other negative results for universal forecasting scheme of ergodic processes.
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