An asymptotic expansion for the distribution of the linear discriminant function based on monotone missing data

DOI10.1080/00949655.2011.633521zbMath1431.62272OpenAlexW1999702046MaRDI QIDQ4913943

Nobumichi Shutoh

Publication date: 17 April 2013

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2011.633521

zbMATH Keywords

asymptotic expansiondiscriminant analysisasymptotic approximationprobabilities of misclassificationmonotone missing data

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Asymptotic distribution theory in statistics (62E20) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Missing data (62D10)

Related Items (2)

Testing equality of two mean vectors with monotone incomplete data ⋮ On the asymptotic distribution of \(T^2\)-type statistic with two-step monotone missing data

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
• An asymptotic approximation for EPMC in linear discriminant analysis based on monotone missing data
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• 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
• Conditional confidence intervals for classification error rate
• Two-Sample Asymptotically Distribution-Free Tests for Incomplete Multivariate Observations
• Errors in Discrimination
• 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
• Discriminant analysis when a block of observations is missing
• Exact misclassification probabilities for plug-in normal quadratic discriminant functions. I: The equal-means case

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