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Edward Ngailo: Discriminant analysis in small and large dimensions

Time: Wed 2017-03-29 15.15

Location: Room 306, House 6, Kräftriket, Department of Mathematics, Stockholm University

Participating: Edward Ngailo (Stockholm University)

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Abstract:
In this article we study the distributional properties of the linear discriminant function under the assumption of the normality by comparing two groups with the same covariance matrix but different mean vectors. A stochastic representation of the discriminant function coefficient is derived which is then used to establish the asymptotic distribution under the high-dimensional asymptotic regime. Moreover, we investigate the classification analysis based on the discriminant function in both small and large dimensions. In the numerical study, a good finite-sample performance of the derived large-dimensional asymptotic distributions is documented.​