Asymptotic approximation of misclassification probabilities in linear discriminant analysis with repeated measurements

Authors

  • Edward K. Ngailo University of Dar Es Salaam
  • Dietrich von Rosen Swedish University of Agricultural Sciences, Linköping University
  • Martin Singull Linköping University

DOI:

https://doi.org/10.12697/ACUTM.2021.25.05

Keywords:

asymptotic approximation, Growth Curve model, linear discriminant function, probability of misclassification

Abstract

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.

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Published

2021-06-21

Issue

Section

Articles