The Annals of Probability

Sufficient Statistics and Extreme Points

E. B. Dynkin

Source: Ann. Probab. Volume 6, Number 5 (1978), 705-730.

Abstract

A convex set $M$ is called a simplex if there exists a subset $M_e$ of $M$ such that every $P \in M$ is the barycentre of one and only one probability measure $\mu$ concentrated on $M_e$. Elements of $M_e$ are called extreme points of $M$. To prove that a set of functions or measures is a simplex, usually the Choquet theorem on extreme points of convex sets in linear topological spaces is cited. We prove a simpler theorem which is more convenient for many applications. Instead of topological considerations, this theorem makes use of the concept of sufficient statistics.

Primary Subjects: 60J50
Secondary Subjects: 60K35, 82A25, 28A65
Keywords: 60-02; Extreme points; sufficient statistics; Gibbs states; ergodic decomposition of an invariant measure; symmetric measures; entrance and exit laws; excessive measures and functions

Full-text: Open access

Links and Identifiers

Permanent link to this document: http://projecteuclid.org/euclid.aop/1176995424
JSTOR: links.jstor.org
Digital Object Identifier: doi:10.1214/aop/1176995424
Mathematical Reviews number (MathSciNet): MR518321
Zentralblatt MATH identifier: 0403.62009


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