Empirical distributions of beliefs under imperfect observation

Olivier Gossner, Tristan Tomala

Research output: Contribution to journalArticlepeer-review

Abstract

Let (xn)n be a process with values in a finite set X and law P, and let yn = f(xn) be a function of the process. At stage n, the conditional distribution pn = P(x n | x1. . . . , xn-1), element of Π = Δ(X), is the belief that a perfect observer, who observes the process online, holds on its realization at stage n. A statistician observing the signals y1, . . ., yn holds a belief en = P(Pn | x1, . . . , xn) ∈ Δ(Π) on the possible predictions of the perfect observer. Given X and f, we characterize the set of limits of expected empirical distributions of the process (e n) when P ranges over all possible laws of (xn) n.

Original languageEnglish (US)
Pages (from-to)13-30
Number of pages18
JournalMathematics of Operations Research
Volume31
Issue number1
DOIs
StatePublished - Feb 2006

Keywords

  • Entropy
  • Repeated games
  • Signals
  • Stochastic process

ASJC Scopus subject areas

  • General Mathematics
  • Computer Science Applications
  • Management Science and Operations Research

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