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Partial Distributional Canonical Discriminant Analysis
Author(s) -
Feldmann Uwe
Publication year - 1993
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.4710350405
Subject(s) - linear discriminant analysis , mathematics , canonical analysis , curse of dimensionality , canonical form , statistics , discriminant , dimension (graph theory) , maximum likelihood , econometrics , artificial intelligence , computer science , combinatorics , pure mathematics
A canonical discriminant technique is proposed which is unrelated to particular distributional assumptions. This approach allows for a data generated choice between ordered, partially ordered and unordered outcomes and remains identifiable in each dimension of the canonical model. The concepts of allocatability and distinguishability of categories are investigated. Maximum likelihood parameter estimation is conducted and inferential tests for the assessment of the dimensionality of the canonical model are derived. The model is applied to the perioperative prediction of risk of death from peritonitis, using real data.