Discriminant analysis of Gaussian spatial data with exponential covariance structure

Abstract

This paper considers the discrimination of the observation of the stationary Gaussian random field belonging to one of two populations with different means and covariance functions. Assumming that covariance functions has exponential structure, the unknown means and covariance parameters are estimated by ML method. Approximation of the expected error rate associated with Bayes plug-in discriminant function is derived.