Open AccessLinear discriminant analysis of spatial Gaussian data with estimated anisotropy ratio
Author(s) -
Lina Dreižienė
Publication year - 2011
Publication title -
lietuvos matematikos rinkinys
Language(s) - English
Resource type - Journals
eISSN - 2335-898X
pISSN - 0132-2818
DOI - 10.15388/lmr.2011.st02
Subject(s) - covariance , covariance function , mathematics , statistics , gaussian , estimator , bayes' theorem , parametric statistics , linear discriminant analysis , anisotropy , covariance mapping , discriminant function analysis , covariance intersection , bayesian probability , physics , quantum mechanics
The paper deals with a problem of classification of Gaussian spatial data into one of two populations specified by different parametric mean models and common geometric anisotropic covariance function. In the case of an unknown mean and covariance parameters the Plug-in Bayes discriminant function based on ML estimators is used. The asymptotic approximation of expected error rate (AER) is derived in the case of unknown mean parameters and single unknown covariance parameter i.e., anisotropy ratio.