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Activity Number: 260
Type: Contributed
Date/Time: Monday, August 1, 2016 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract #320387
Title: On Estimation of the Specification of Random Fields
Author(s): Zsolt Talata*
Companies: University of Kansas
Keywords: Gibbs fields ; one-point specification ; Markov random fields ; basic neighborhood ; model selection

For random fields on the d-dimensional integer lattice with finite state space, the basic neighborhood is the smallest region that determines the conditional distribution at a site given the values at all other sites. For variable basic neighborhood random fields the basic neighborhood may vary with the values at the surrounding sites, and the sets of the values in these basic neighborhoods are called context blocks. The context blocks may be infinite. Statistical estimation of the context block system of a random field from a sample, a single realization of the random field observed in a finite region, is addressed. The Optimal Likelihood Ratio (OLR) estimator is introduced. Its nearly linear computation complexity is shown and a bound on the probability of the estimation error is proved that implies strong consistency of the estimator.

Authors who are presenting talks have a * after their name.

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