Subspace clustering for the finite mixture of generalized hyperbolic distributions

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The finite mixture of generalised hyperbolic distributions is a flexible model for clustering, but its large number of parameters for estimation, especially in high dimensions, can make it computationally expensive to work with. In light of this issue, we provide an extension of the subspace clustering technique developed for finite Gaussian mixtures to that of generalised hyperbolic distribution. The methodology will be demonstrated with numerical experiments.