PUGMM

Finite Gaussian mixture models with parsimonious extended ultrametric covariance structures estimated via a grouped coordinate ascent algorithm, which is equivalent to the Expectation-Maximization algorithm. The thirteen ultrametric covariance structures implemented allow for the inspection of different hierarchical relationships among variables. The estimation of an ultrametric correlation matrix is included as a function. The methodologies are described in Cavicchia, Vichi, Zaccaria (2024) doi:10.1007/s11222-024-10405-9, Cavicchia, Vichi, Zaccaria (2022) doi:10.1007/s11634-021-00488-x and Cavicchia, Vichi, Zaccaria (2020) doi:10.1007/s11634-020-00400-z.

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