Linear discriminant analysis of spatial Gaussian data with estimated anisotropy ratio
Articles
Lina Dreižienė
Klaipėda University
Published 2011-12-15
https://doi.org/10.15388/LMR.2011.st02
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Keywords

Bayesian discriminant function
actual risk
expected risk
anisotropy ratio
Gaussian random field

How to Cite

Dreižienė L. (2011) “Linear discriminant analysis of spatial Gaussian data with estimated anisotropy ratio”, Lietuvos matematikos rinkinys, 52(proc. LMS), pp. 315–320. doi: 10.15388/LMR.2011.st02.

Abstract

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.

 

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