Statistical estimation with bounded memory

Leonid Kontorovich

doi:10.1007/s11222-011-9293-5

Statistical estimation with bounded memory

Leonid Kontorovich

Department of Computer Science

Ben-Gurion University of the Negev

Research output: Contribution to journal › Article › peer-review

Abstract

We investigate bounded-memory estimators of statistical functionals. It is shown that, for nondegenerate functionals and stochastic processes, it is impossible to achieve consistent estimation with bounded memory. In the positive direction, we show that O(log(1/ε)) states suffice to achieve ε-consistent estimation for a natural class of functionals. A canonical optimal construction is conjectured for arbitrary statistical functionals.

Original language	American English
Pages (from-to)	1155-1164
Number of pages	10
Journal	Statistics and Computing
Volume	22
Issue number	5
DOIs	https://doi.org/10.1007/s11222-011-9293-5
State	Published - 1 Sep 2012

Keywords

Automaton
Bounded memory
DFA
Regular approximation
Statistical estimation

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Statistics and Probability
Statistics, Probability and Uncertainty
Computational Theory and Mathematics

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10.1007/s11222-011-9293-5

Cite this

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AB - We investigate bounded-memory estimators of statistical functionals. It is shown that, for nondegenerate functionals and stochastic processes, it is impossible to achieve consistent estimation with bounded memory. In the positive direction, we show that O(log(1/ε)) states suffice to achieve ε-consistent estimation for a natural class of functionals. A canonical optimal construction is conjectured for arbitrary statistical functionals.

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KW - Bounded memory

KW - DFA

KW - Regular approximation

KW - Statistical estimation

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Statistical estimation with bounded memory

Abstract

Keywords

All Science Journal Classification (ASJC) codes

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