Classification With the Matrix-Variate-t Distribution Article Swipe

View

Related Concepts

Random variate Matrix (chemical analysis) Distribution (mathematics) Statistics Mathematics Computer science Chemistry Chromatography Mathematical analysis Random variable

Geoffrey Z. Thompson , Ranjan Maitra , William Q. Meeker , Ashraf Bastawros ·

YOU? · · 2021 · Open Access · · DOI: https://doi.org/10.6084/m9.figshare.11114498 · OA: W4394442401

Matrix-variate distributions can intuitively model the dependence structure of matrix-valued observations that arise in applications with multivariate time series, spatio-temporal, or repeated measures. This article develops an expectation-maximization algorithm for discriminant analysis and classification with matrix-variate <i>t</i>-distributions. The methodology shows promise on simulated datasets or when applied to the forensic matching of fractured surfaces or to the classification of functional magnetic resonance, satellite, or hand gestures images. Supplementary materials for this article are available online.