An asymptotic approximation for EPMC in linear discriminant analysis based on two-step monotone missing samples

In this paper, we consider the expected probabilities of misclassification (EPMC) in the linear discriminant function (LDF) based on two-step monotone missing samples and derive an asymptotic approximation for the EPMC with an explicit form for the considered LDF. For this purpose, we also provide some results of the expectations for the inverted Wishart matrices in this paper. Finally, we conduct the Monte Carlo simulation for evaluating our result.

MoreLess

Year of publication:	2011
Authors:	Shutoh, Nobumichi ; Hyodo, Masashi ; Seo, Takashi
Published in:	Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 102.2011, 2, p. 252-263
Publisher:	Elsevier
Keywords:	Linear discriminant analysis Expected probability of misclassification Asymptotic approximation Monotone missing samples

More details

Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10008861545