An EM Gradient Algorithm for Mixture Models with Components Derived from the Manly Transformation
<|reference_start|>An EM Gradient Algorithm for Mixture Models with Components Derived from the Manly Transformation: Zhu and Melnykov (2018) develop a model to fit mixture models when the components are derived from the Manly transformation. Their EM algorithm utilizes Nelder-Mead optimization in the M-step to update the skew parameter, $\boldsymbol{\lambda}_g$. An alternative EM gradient algorithm is proposed, using one step of Newton's method, when initial estimates for the model parameters are good.<|reference_end|>
@article{clark2024an,
    title={An EM Gradient Algorithm for Mixture Models with Components Derived from
  the Manly Transformation},
    author={Katharine M. Clark and Paul D. McNicholas},
    journal={arXiv preprint arXiv:2410.00848},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.00848},
    primaryClass={stat.ML cs.LG}
}