Paper Info
Title
Asymptotic Expansion of the Distribution of the Studentized Linear Discriminant Function Based on Two-Step Monotone Missing Samples
Abstract
This article proposes an asymptotic expansion for the Studentized linear discriminant function using two-step monotone missing samples under multivariate normality. The asymptotic expansions related to discriminant function have been obtained for complete data under multivariate normality. The result derived by Anderson (1973) plays an important role in deciding the cut-off point that controls the probabilities of misclassification. This article provides an extension of the result derived by Anderson (1973) in the case of two-step monotone missing samples under multivariate normality. Finally, numerical evaluations by Monte Carlo simulations were also presented.
Year
DOI
Venue
2010
10.1080/03610918.2010.493275
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
Keywords
DocType
Volume
Asymptotic approximation,Asymptotic expansion,Linear discriminant analysis,Monotone missing samples,Probabilities of misclassification
Journal
39
Issue
ISSN
Citations 
7
0361-0918
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Nobumichi Shutoh101.01
Takashi Seo203.04