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March 2017 EPMC estimation in discriminant analysis when the dimension and sample sizes are large
Tetsuji Tonda, Tomoyuki Nakagawa, Hirofumi Wakaki
Hiroshima Math. J. 47(1): 43-62 (March 2017). DOI: 10.32917/hmj/1492048847

Abstract

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.

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Tetsuji Tonda. Tomoyuki Nakagawa. Hirofumi Wakaki. "EPMC estimation in discriminant analysis when the dimension and sample sizes are large." Hiroshima Math. J. 47 (1) 43 - 62, March 2017. https://doi.org/10.32917/hmj/1492048847

Information

Received: 15 April 2016; Revised: 25 October 2016; Published: March 2017
First available in Project Euclid: 13 April 2017

zbMATH: 1365.62250
MathSciNet: MR3634261
Digital Object Identifier: 10.32917/hmj/1492048847

Subjects:
Primary: 62H30
Secondary: 62F12

Rights: Copyright © 2017 Hiroshima University, Mathematics Program

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Vol.47 • No. 1 • March 2017
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