An EM Gradient Algorithm for Mixture Models with Components Derived from the Manly Transformation
Abstract
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, λg. An alternative EM gradient algorithm is proposed, using one step of Newton's method, when initial estimates for the model parameters are good.
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