Background noise in cluster analyses can potentially mask the true underlying patterns. To tease out patterns uniquely to certain populations, a Bayesian semi-parametric clustering method is presented. It infers and adjusts background noise. The method is built upon a mixture of the Dirichlet process and a point mass function. Simulations demonstrate the effectiveness of the proposed method. The method is then applied to analyze a longitudinal data set on allergic sensitization and asthma status.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5464744 | PMC |
| http://dx.doi.org/10.1016/j.csda.2016.11.009 | DOI Listing |
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