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, $\hat{\mathbf{I}}{»}_g$. An alternative EM gradient algorithm is proposed, using one step of Newton's method, when initial estimates for the model parameters are good.