Title: A multithreaded implementation of the EM algorithm for finite mixture models
Authors: Geoffrey McLachlan - University of Queensland (Australia) [presenting]
Abstract: Finite mixture distributions provide a flexible tool for modelling heterogeneous data. However, parameter estimation via the EM algorithm can become very time-consuming due to the complicated expressions involved on the E-step that are numerically expensive to evaluate. We develop a block implementation of the EM algorithm that facilitates the calculations on the E- and M-steps to be spread across a larger number of threads. We focus on the fitting of finite mixtures of multivariate skew normal and skew t-distributions, and show that both the E- and M-steps in the EM algorithm can be modified to allow the data to be split into blocks. The approach can be easily implemented for use by multicore and multiprocessor machines. The improvement in time performance is illustrated on some real data sets.