DISCRIMINACIÓN CUADRÁTICA MEDIANTE MATRICES DE COVARIANZAS
DOI:
https://doi.org/10.15381/pes.v1i2.9210Abstract
Maximizando y minimizando la función
aS1a
dS2a
donde S1 y S2 son las matrices de covarianzas muéstrales de dos poblaciones p-variantes, con vectores de medias iguales o diferentes, se consiguen dos combinaciones lineales de las componentes del vector p-variante.
Si los dos grupos tienen estructuras de dispersiones diferentes, esas combinaciones son usadas para la clasificación de individuos que proceden de una de dos poblaciones normales multivariantes. Este método comparado con el método de clasificación usando el cociente de verosimilitudes (Mardia, 1976), para poblaciones normales simuladas por Monte Carlo con p=2, p=3 y p=4, resultan equivalentes.
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Copyright (c) 1998 Doris Gómez Ticerán
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