We consider the fitting of normal or t-component mixturemodels to multivariate data, using maximum likelihood via the EM algorithm. This approach requires the initial specification of an initial estimate of the vector of unknown parameters, or equivalently, of an initial classification of the data with respect to the components of the mixturemodel under fit. We describe an algorithm called EMMIX that automatically undertakes this fitting, including the provision of suitable initial values if not supplied by the user. The EMMIX algorithm has several options, including the option to carry out a resampling-based test for the number of components in the mixture model
