On the upper bound of the number of modes of a multivariate normal mixture

نویسندگان

  • Surajit Ray
  • Dan Ren
چکیده

The main result of this article states that one can get as many as D + 1 modes from just a two component normal mixture in D dimensions. Multivariate mixture models are widely used for modeling homogeneous populations and for cluster analysis. Either the components directly or modes arising from these components are often used to extract individual clusters. Although in lower dimensions these strategies work well, our results show that high dimensional mixtures are often very complex and researchers should take extra precautions when using these for cluster analysis. Even in the simplest case of mixing only two normal components in D dimensions one can generate D + 1 modes. When the components are non-normal or if we have more than two components the number of modes are bound to be even larger, which might lead us to incorrect inference on the number of clusters. Further analysis shows that the number of modes depends on the component means and eigenvalues of the ratio of the two component covariance matrices, which in turn provides a clear guideline as to when one can use mixture analysis for clustering high dimensional data.

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عنوان ژورنال:
  • J. Multivariate Analysis

دوره 108  شماره 

صفحات  -

تاریخ انتشار 2012