אריה קנטורוביץ

אקדמי בכיר

Statistical estimation with bounded memory

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.

שפת פרסום אנגלית
דפים 1155-1164
כתב עת Statistics and Computing
כרך 22
נושא מספר 5
סטטוס פרסום פורסם - 01.09.2012

Keywords

Automaton
Bounded memory
DFA
Regular approximation
Statistical estimation

ASJC Scopus subject areas

Theoretical Computer Science
Statistics and Probability
Statistics, Probability and Uncertainty
Computational Theory and Mathematics
גישה למסמך
10.1007/s11222-011-9293-5
קבצים וקישורים אחרים
Link to publication in Scopus