Journal
METRON-INTERNATIONAL JOURNAL OF STATISTICS
Volume 73, Issue 2, Pages 177-199Publisher
SPRINGER-VERLAG ITALIA SRL
DOI: 10.1007/s40300-015-0064-5
Keywords
Integrated completed likelihood; Finite mixture models; Model-based clustering; Greedy search
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Funding
- Science Foundation Ireland [SFI/12/RC/2289, 12/IP/1424]
- Science Foundation Ireland (SFI) [12/IP/1424] Funding Source: Science Foundation Ireland (SFI)
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The integrated completed likelihood (ICL) criterion has proven to be a very popular approach in model-based clustering through automatically choosing the number of clusters in a mixture model. This approach effectively maximises the complete data likelihood, thereby including the allocation of observations to clusters in the model selection criterion. However for practical implementation one needs to introduce an approximation in order to estimate the ICL. Our contribution here is to illustrate that through the use of conjugate priors one can derive an exact expression for ICL and so avoiding any approximation. Moreover, we illustrate how one can find both the number of clusters and the best allocation of observations in one algorithmic framework. The performance of our algorithm is presented on several simulated and real examples.
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