Simultaneous Gaussian model-based clustering for samples of multiple origins

@article{Lourme2013SimultaneousGM,
  title={Simultaneous Gaussian model-based clustering for samples of multiple origins},
  author={Alexandre Lourme and Christophe Biernacki},
  journal={Computational Statistics},
  year={2013},
  volume={28},
  pages={371-391}
}
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 unrelated: All individuals are described by the same features and partitions of identical meaning are expected. Justifying from some natural arguments a stochastic linear link between the components of… CONTINUE READING

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