Simultaneous Gaussian model-based clustering for samples of multiple origins

• Published in: Computational statistics Vol. 28; no. 1; pp. 371 - 391
• Main Authors: Lourme, A., Biernacki, C.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer-Verlag 01.02.2013; Springer Nature B.V; Springer Verlag
• Subjects: Birds; Cluster analysis; Clustering; Datasets; Economic Theory/Quantitative Economics/Mathematical Methods; Gaussian; Links; Mathematical models; Mathematics and Statistics; Maximization; Methodology; Original Paper; Partitioning; Partitions; Principal components analysis; Probability and Statistics in Computer Science; Probability Theory and Stochastic Processes; Statistical analysis; Statistics; Stochastic models; Studies; United States > US; Gaussian mixture; Model selection; EM algorithm; Biological features; Stochastic linear link; Model-based clustering

Gaussian mixture model-based clustering is now a standard tool to estimate some hypothetical underlying partition of a single dataset. In this paper, we aim to cluster several different datasets at the same time in a context where underlying populations, even though different, are not completely unr...