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

Sammanfattning

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.

Nyckelord

Asymptotic approximation; Growth Curve model; linear discriminant function; probability of misclassification

Publicerad i

Acta et Commentationes Universitatis Tartuensis de Mathematica
2021, Volym: 25, nummer: 1, sidor: 67-85 Utgivare: UNIV TARTU PRESS

SLU författare

• von Rosen, Dietrich

  • Institutionen för energi och teknik, Sveriges lantbruksuniversitet
    
  • Linköpings universitet

UKÄ forskningsämne

Sannolikhetsteori och statistik


Publikationens identifierare

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

Permanent länk till denna sida (URI)

https://res.slu.se/id/publ/123255