An asymptotic approximation for EPMC in linear discriminant analysis based on monotone missing data

DOI10.1016/j.jspi.2011.07.001zbMath1225.62088OpenAlexW2034827691MaRDI QIDQ643381

Nobumichi Shutoh

Publication date: 28 October 2011

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2011.07.001

zbMATH Keywords

asymptotic approximationsprobabilities of misclassification

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Monte Carlo methods (65C05)

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Cites Work

• An asymptotic approximation for EPMC in linear discriminant analysis based on two-step monotone missing samples
• Asymptotic expansions relating to discrimination based on two-step monotone missing samples
• Discrimination of observations into one of two elliptic populations based on monotone training samples
• Errors in discrimination with monotone missing data from multivariate normal populations
• Discriminant analysis under elliptical populations
• Some Basic Properties of the Mle's for a Multivariate Normal Distribution with Monotone Missing Data
• Asymptotic aproximations for EPMC’s of the linear and the quadratic discriminant functions when the sample sizes and the dimension are large
• An Asymptotic Expansion for the Distribution of the Linear Discriminant Function
• Multivariate Statistics