Asymptotic approximation of misclassification probabilities in linear discriminant analysis with repeated measurements
2021 ◽
Vol 25
(1)
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pp. 67-85
Keyword(s):
We propose asymptotic approximations for the probabilities of misclassification in linear discriminant analysis when the group means follow a growth curve structure. The discriminant function can classify a new observation vector of p repeated measurements into one of several multivariate normal populations with equal covariance matrix. We derive certain relations of the statistics under consideration in order to obtain asymptotic approximation of misclassification errors for the two group case. Finally, we perform Monte Carlo simulations to evaluate the reliability of the proposed results.
2011 ◽
Vol 102
(2)
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pp. 252-263
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2012 ◽
Vol 142
(1)
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pp. 110-125
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2013 ◽
Vol 2013
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pp. 1-7
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2019 ◽
Vol 7
(5)
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pp. 1720-1725
2009 ◽
Vol 29
(10)
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pp. 2781-2785
2020 ◽
Vol 16
(8)
◽
pp. 1079-1087