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