Computational limits to nonparametric estimation for ergodic processes

Hayato Takahashi

doi:10.1109/tit.2011.2165791

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arXiv · 1002.1559

Computational limits to nonparametric estimation for ergodic processes

Hayato Takahashi

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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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Hayato Takahashi. 2011-01-11. Computational limits to nonparametric estimation for ergodic processes. https://doi.org/10.1109/tit.2011.2165791

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