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An extension of geisser's discrimination model to proportional covariance matrices
Author(s) -
Hawkins Douglas M.,
Raath E. Liefde
Publication year - 1982
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.2307/3556192
Subject(s) - homoscedasticity , covariance , extension (predicate logic) , mathematics , statistics , computer science , heteroscedasticity , programming language
The predictive discrimination model of Geisser is derived for the case in which the covariance matrices of the different populations are assumed proportional, with unknown constants of proportionality. It is shown that this model provides a better fit to a set of data than does the usual homoscedastic model.