Title: Handling Outliers in Model-Based Clustering
Abstract: An algorithm for handling outliers in multivariate model-based clustering is introduced. The algorithm, called OCLUST, is based on the distribution of subset log-likelihoods and does not require pre-specification of the proportion of outliers. The OCLUST algorithm is demonstrated on simulated and real data before an extension to three-way data is discussed and briefly illustrated.
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