INFORMATICA

Informatica

0868-49520868-4952

INFO1061

10.15388/Informatica.2015.64

Research Article

Actual Error Rates in Classification of the T-Distributed Random Field Observation Based on Plug-in Linear Discriminant Function

Dučinskas

Kęstutis

kestutis.ducinskas@ku.lt Zikarienė

Eglė

egle.zikariene@gmail.com* Department of Mathematics and Statistics, Klaipeda University, H. Manto 84, 92294 Klaipeda, Lithuania Recognition Processes Department, Institute of Mathematics and Informatics, Vilnius University, Akademijos 4, 08663 Vilnius, Lithuania

*Corresponding author.

01012015

2645575680108 20140103 2015

Vilnius University

2015

In current paper a problem of classification of T-distributed random field observation into one of two populations specified by common scaling function is considered. The ML and LS estimators of the mean parameters are plugged into the linear discriminant function. The closed form expressions for the Bayes error rate and the actual error rate associated with the aforementioned discriminant functions are derived. This is the extension of one for the Gaussian case. The actual error rates are used to evaluate and compare the performance of the plug-in discriminant function by means of Monte Carlo study.

Keywords T-distributed random field Bayes rule spatial correlation scaling function actual error rate