Empirical Distributions of Beliefs Under Imperfect Observation

Olivier Gossner and Tristan Tomala

Post-Print from HAL

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(xn | x1,...,xn–1), element of = (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) () 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 (en) when P ranges over all possible laws of (xn)n.

Keywords: stochastic process; signals; entropy; repeated games (search for similar items in EconPapers)
Date: 2006-02
References: Add references at CitEc
Citations: View citations in EconPapers (12)

Published in Mathematics of Operations Research, 2006, Vol.31,n°1, pp.13-30. ⟨10.1287/moor.1050.0174⟩

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-00487960

DOI: 10.1287/moor.1050.0174

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD (hal@ccsd.cnrs.fr).