von Rosen, Dietrich
- Department of Energy and Technology, Swedish University of Agricultural Sciences
Research article2023Peer reviewedOpen access
An Edgeworth-type expansion for the distribution of a likelihood-based discriminant function
Gasana, Emelyne Umunoza; von Rosen, Dietrich; Singull, Martin
Abstract
The exact distribution of a classification function is often complicated to allow for easy numerical calculations of misclassification errors. The use of expansions is one way of dealing with this difficulty. In this paper, approximate probabilities of misclassification of the maximum likelihood-based discriminant function are established via an Edgeworth-type expansion based on the standard normal distribution for discriminating between two multivariate normal populations.
Keywords
Classification rule; discriminant analysis; Edgeworth-type expansion; missclassification errors
Published in
Journal of Statistical Computation and Simulation
2023, Volume: 93, number: 17, pages: 3185-3202
Publisher: TAYLOR AND FRANCIS LTD
SLU Authors
UKÄ Subject classification
Probability Theory and Statistics
Publication identifier
DOI: https://doi.org/10.1080/00949655.2023.2219358
Permanent link to this page (URI)
https://res.slu.se/id/publ/122695