Sequential Dirichlet process mixtures of multivariate skew \(t\)-distributions for model-based clustering of flow cytometry data

DOI10.1214/18-AOAS1209zbMath1417.62310arXiv1702.04407MaRDI QIDQ2415485

Boris P. Hejblum, François Caron, Rodolphe Thiébaut, Chariff Alkhassim, Raphael Gottardo

Publication date: 22 May 2019

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1702.04407

zbMATH Keywords

Bayesian nonparametricsDirichlet processHIVflow cytometrymixture modelsequentialskew \(t\)-distributionautomatic gating

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Sequential estimation (62L12)

Related Items (3)

Infinite mixtures of multivariate normal-inverse Gaussian distributions for clustering of skewed data ⋮ Flexible Modelling via Multivariate Skew Distributions ⋮ CytOpT: Optimal Transport with Domain Adaptation for Interpreting Flow Cytometry data

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