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Robust Classification via Finite Mixtures of...
Journal article

Robust Classification via Finite Mixtures of Matrix Variate Skew-t Distributions

Abstract

Analysis of matrix variate data is becoming increasingly common in the literature, particularly in the field of clustering and classification. It is well known that real data, including real matrix variate data, often exhibit high levels of asymmetry. To address this issue, one common approach is to introduce a tail or skewness parameter to a symmetric distribution. In this regard, we introduce here a new distribution called the matrix variate …

Authors

Mahdavi A; Balakrishnan N; Jamalizadeh A

Journal

Mathematics, Vol. 12, No. 20,

Publisher

MDPI

DOI

10.3390/math12203260

ISSN

2227-7390

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