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Interval estimation in two-group discriminant analysis under heteroscedasticity for large dimension

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  • Takayuki Yamada

Abstract

This article is concerned with the problem of discriminating between two populations with heteroscedastic multivariate normal distributions based on an observation vector x$\mbox{$\boldsymbol{x}$}$. We give the limiting distribution of the unbiased estimator for the log odds ratio of the posterior probabilities as the sample sizes Ni (i = 1, 2) and the dimension p go to infinity together with the ratio p/(Ni − 1) converging a finite non zero constant ci ∈ (0, 1) for the case in which the prior probabilities are equal. Approximated interval estimation for the log odds ratio is derived. Simulation results indicate that our estimation has good accuracy compared with the classical results.

Suggested Citation

  • Takayuki Yamada, 2018. "Interval estimation in two-group discriminant analysis under heteroscedasticity for large dimension," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 47(23), pages 5717-5728, December.
    • Handle: RePEc:taf:lstaxx:v:47:y:2018:i:23:p:5717-5728
    DOI: 10.1080/03610926.2017.1400060
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