Constrained linear discriminant rule via the Studentized classification statistic based on monotone missing data
2012 (English)In: SUT Journal of Mathematics, ISSN 0916-5746, Vol. 48, no 1, 55-69 p.Article in journal (Refereed) Published
This paper provides an asymptotic expansion for the distribution of the Studentized linear discriminant function with k-step monotone missing training data. It turns out to be a certain generalization of the results derived by Anderson  and Shutoh and Seo . Furthermore we also derive the cutoff point constrained by a conditional probability of misclassification using the idea of McLachlan . Finally we perform Monte Carlo simulation to evaluate our results.
Place, publisher, year, edition, pages
2012. Vol. 48, no 1, 55-69 p.
Asymptotic expansion, Linear discriminant analysis, Monotone missing data, Probabilities of misclassification
IdentifiersURN: urn:nbn:se:kth:diva-129794ScopusID: 2-s2.0-84879267361OAI: oai:DiVA.org:kth-129794DiVA: diva2:654637
QC 201310082013-10-082013-10-042014-05-09Bibliographically approved