Hiroshima Mathematical Journal
- Hiroshima Math. J.
- Volume 47, Number 1 (2017), 43-62.
EPMC estimation in discriminant analysis when the dimension and sample sizes are large
In this paper we obtain a higher order asymptotic unbiased estimator for the expected probability of misclassification (EPMC) of the linear discriminant function when both the dimension and the sample size are large. Moreover, we evaluate the mean squared error of our estimator. We also present a numerical comparison between the performance of our estimator and that of the other estimators based on Okamoto (1963, 1968) and Fujikoshi and Seo (1998). It is shown that the bias and the mean squared error of our estimator are less than those of the other estimators.
Hiroshima Math. J. Volume 47, Number 1 (2017), 43-62.
Received: 15 April 2016
Revised: 25 October 2016
First available in Project Euclid: 13 April 2017
Permanent link to this document
Zentralblatt MATH identifier
Tonda, Tetsuji; Nakagawa, Tomoyuki; Wakaki, Hirofumi. EPMC estimation in discriminant analysis when the dimension and sample sizes are large. Hiroshima Math. J. 47 (2017), no. 1, 43--62.https://projecteuclid.org/euclid.hmj/1492048847