Moments of the likelihood-based discriminant function

Abstract

The likelihood approach used in this paper leads to quadratic discriminant functions. Classification into one of two known multivariate normal populations with a known and unknown covariance matrix are separately considered, where the two cases depend on the sample size and an unknown squared Mahalanobis distance. Their exact distributions are complicated to obtain. Therefore, moments for the likelihood based discriminant functions are established to express the basic characteristics of respective distribution.

Keywords

classification; discriminant function; maximum likelihood; moments

Published in

Communications in Statistics - Theory and Methods
2024, volume: 53, number: 3, pages: 1122-1134
Publisher: TAYLOR AND FRANCIS INC

SLU Authors

• von Rosen, Dietrich

  • Department of Energy and Technology, Swedish University of Agricultural Sciences
    
  • Linköping University

UKÄ Subject classification

Probability Theory and Statistics

Publication identifier

• DOI: https://doi.org/10.1080/03610926.2022.2100909

Permanent link to this page (URI)

https://res.slu.se/id/publ/118618