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arXiv Machine Learning By Katharine M. Clark, Paul D. McNicholas

FastManly: An EM-Gradient Algorithm for Manly Mixture Models

Read the original on arXiv Machine Learning →

FastManly is a new implementation of mixtures of Manly transformations that replaces the Nelder–Mead optimization used in traditional EM algorithms with Newton’s method. The authors derive both the gradient and full Hessian for the EM–gradient algorithm. Simulation studies demonstrate that FastManly achieves improved performance and noticeable speedups compared to the conventional approach.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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