Robustness of the linear discriminant function to nonnormality: Edgeworth series distribution

DOI10.1016/0378-3758(78)90024-1zbMath0375.62054OpenAlexW2032423551MaRDI QIDQ1245661

Kocherlakota Subrahmaniam, Enock F. Chinganda

Publication date: 1978

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(78)90024-1

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (9)

The performance of the linear and quadratic discriminant functions for three types of non-normal distribution ⋮ On the errors of misclassification based on dichotomous and normal variables ⋮ Effects of unlabeled data on classification error in normal discriminant analysis ⋮ Errors of misclassification associated with the inverse gaussion distribution ⋮ Errors of misclassification in discrimination with data from truncated \(t\) populations ⋮ On the Behavior of the Distributions of the Probabilities of Misclassification in the use of the Linear Discriminant Function Under Multinonnormality ⋮ Errors in discrimination with monotone missing data from multivariate normal populations ⋮ Robustness of the linear discriminant function to nonnormality: Johnson's system ⋮ Application of box-cox transformations to discrimination for the two-class problem

Cites Work

• Robustness of the linear discriminant function to nonnormality: Johnson's system
• Estimation of the probabilities of misclassification for a linear discriminant function in the univariate normal case
• Errors in Discrimination
• THE DISTRIBUTION OF ‘STUDENT'S’ t IN RANDOM SAMPLES OF ANY SIZE DRAWN FROM NON-NORMAL UNIVERSES
• The conditions under which Gram-Charlier and Edgeworth curves are positive definite and unimodal
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