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Abstract : |
We consider the fitting of normal mixture models to multivariate data, using maximum likelihood via the EM algorithm. This approach requires the specification of an initial estimate of the vector of unknown parameters, or equivalently, of an initial classification of the data with respct to the components of the mixture model under fit. We describe an algorithm called MIXFIT that automatically undertakes this fitting, including the specification of suitable initial values if not supplied by the user. The MIXFIT algorithm has several options, including the provision to carry out a resampling-based test for the number of components in the mixture model. EM algorithm; Cluster analysis; Likelihood ratio test, |
